Here's a concise summary of US Patent 7333511, along with a plain-language overview of its independent claims:

US Patent 7333511 Summary

• Title: Dynamically channelizable packet transport network
• Assignee: The current assignees listed are Optimum Communications Services Inc, A Delaware Corp; Mark Sandstrom; and Xenogenic Development LLC. The original assignee was Optimum Communications Services Inc Canada.
• Inventor: Mark Henrik Sandstrom
• Filing Date: August 29, 2002
• Issue Date: February 19, 2008
• Abstract: The patent describes a communications network for transferring data packets between Layer 2 (L2) and Layer 3 (L3) nodes using dynamically channelizable multi-source buses at Layer 1 (L1). A control process periodically optimizes how the bus capacity is allocated among its source nodes based on real-time traffic demand. This aims to maximize data throughput for dynamic packet traffic, such as Internet traffic, by adaptively allocating transport network capacity.

Legal Status and Litigation:

The patent's legal status is "Expired - Lifetime", with an expiration date of July 30, 2025. As of April 26, 2026, the patent has expired.

Litigation related to this patent has been filed in various courts in 2024, including the Virginia Eastern District Court, Minnesota District Court, and the International Trade Commission. No specific dockets for the Court of Appeals for the Federal Circuit (CAFC) in 2026 were found in the provided patent information or during the search.

Plain-Language Overview of Independent Claims:

• Independent Claim 1 (Network System): This claim describes a network system designed to boost data throughput by flexibly adjusting connection capacities based on demand. It includes:

  • Nodes: A collection of network points, including "source nodes" (sending data) and a "destination node" (receiving data). Each source node indicates its required capacity to the destination.
  • Logical Data Bus: A virtual pathway that carries data packets from the source nodes to the destination. This bus has a total capacity that can be divided into individual "source node specific connections." These connections have adjustable bandwidth and transport data without any higher-level (packet-layer) processing occurring along the connection itself.
  • Digital Logic: Intelligence at the destination node that manages the bus's total capacity. It allocates this capacity among the source nodes by altering the bandwidth of their specific connections, primarily based on their stated capacity demands.

• Independent Claim 20 (Method for Allocating Bandwidth): This claim outlines a method for managing how bandwidth is distributed on a packet transport bus. The method is repeated regularly and involves:

  • Bus Setup: A bus with multiple data sources and a single destination, offering dedicated, flexible-bandwidth channels from each source to the destination. Each source has a specific data traffic load or demand towards the destination.
  • Allocation: The destination of the bus distributes the total bus bandwidth among the individual sources, taking into account their traffic demands.
  • Assignment: The destination then assigns specific units of bandwidth to each source's channel according to this allocation.
  • Transport: Data packets are then sent over the bus from the source nodes to the destination based on these assigned bandwidth units.

• Independent Claim 29 (Process for Optimizing Capacity Allocation): This claim describes a recurring process for optimizing how capacity is allocated within a data transport network system. The system has "ingress interfaces" (entry points for data), an "egress interface" (exit point for data), and a "capacity pool" for moving data from ingress to egress. Each cycle of the process includes:

  • Optimizing Allocation: The egress interface determines the best way to distribute the available capacity among the individual ingress interfaces for data transfer. This decision is largely based on how much capacity each ingress interface requires.
  • Assigning Capacity Units: Based on this optimization, the egress interface then assigns specific units of capacity from the pool to each ingress interface.
  • Transporting Data: Data packets are then transported from the ingress interfaces to the egress interface using these assigned capacity units.

As of April 26, 2026, the provided patent information and search results indicate ongoing litigation involving US Patent 7333511.

Here is a summary of the known litigation:

• Plaintiff(s): Not explicitly stated in the provided snippets, but "Inventors" are mentioned as filing suit against the USPTO patent invalidation program, which may relate to the context of patent validity challenges.
• Defendant(s): Not explicitly stated in the provided snippets, but "large corporations" and the "US Patent Office (USPTO)" are mentioned as entities against whom inventors are fighting in the context of patent validity challenges.
• Jurisdiction:
  • Virginia Eastern District Court
  • Minnesota District Court
  • International Trade Commission
• Case Number:
  • 1:24-cv-01687 (Virginia Eastern District Court)
  • 1:24-cv-01682 (Virginia Eastern District Court)
  • 1:24-cv-01681 (Virginia Eastern District Court)
  • 0:24-cv-03118 (Minnesota District Court)
  • 0:24-cv-03053 (Minnesota District Court)
  • 0:24-cv-02796 (Minnesota District Court)
  • 337-TA-370 (International Trade Commission)
  • 337-TA-1384 (International Trade Commission)
• Filing Date: All listed cases were filed in 2024.
• Outcome or Current Status: The provided information indicates that litigation is ongoing, with cases filed in various district courts and the International Trade Commission. The general context of some search results suggests challenges against patent validity, but specific outcomes for these particular cases are not detailed.

Proceedings overview

As of July 21, 2026, there are no AIA trial proceedings (Inter Partes Review, Post-Grant Review, or Covered Business Method) on file for US Patent 7333511 according to the USPTO Open Data Portal and subsequent web searches. This means all claims of US7333511 remain untested by PTAB challenges.

Strategic summary

All claims (1-41) of US7333511 are currently untested by any AIA trial proceedings. There is no estoppel landscape established through PTAB decisions. The absence of PTAB activity, particularly for a patent that has been involved in district court and ITC litigation in 2024, is noteworthy. It suggests that either potential petitioners have not yet identified strong prior art grounds for an AIA challenge, or that the litigation strategy of the parties involved has not led to the filing of such petitions.

Recommended next steps

Since no PTAB activity exists, a defendant facing assertion of this patent would have all prior art grounds available for a potential IPR, PGR, or CBM challenge, assuming the relevant statutory deadlines for filing are met. The absence of PTAB activity means the patent claims have not been subjected to the scrutiny of an AIA trial, and their validity under Sections 102, 103, or 112 (for PGR/CBM) remains unconfirmed by the Board. If considering a challenge, a thorough prior art search would be the crucial first step.

Inventors

• Mark Henrik Sandstrom (Optimum Communications Services Inc Canada at the time of filing)

Original assignee

The original assignee, Optimum Communications Services Inc Canada, appears to have been an operating company. The patent describes "communications network for transporting data packets" and "providing the desired connectivity... among the client sites," suggesting a focus on network infrastructure and services. However, current information on its products embodying the claims and its current operating status is not readily determinable from the provided patent text or initial search results.

Assignment timeline

• 2003-10-01 (executed) / recorded 2003-10-01
  • Conveyance: Assignment
  • Assignor: Sandstrom, Mark
  • Assignee: Optimum Communications Technologies, Inc.
  • Correspondent: Not specified in the provided text.
  • Context: Transfer from inventor to a related corporate entity.
• 2006-03-03 (executed) / recorded 2006-03-03
  • Conveyance: Assignment
  • Assignor: Optimum Communications Technologies, Inc.
  • Assignee: Optimum Communications Services, Inc.
  • Correspondent: Not specified in the provided text.
  • Context: Internal corporate reorganization/transfer between related entities.
• 2012-07-05 (executed) / recorded 2012-07-05
  • Conveyance: Assignment
  • Assignor: Optimum Communications Services, Inc.
  • Assignee: Optimum Communications Services, Inc.
  • Correspondent: Not specified in the provided text.
  • Context: Appears to be a re-recording or clarification of ownership for the same entity.
• 2012-07-17 (executed) / recorded 2012-07-17
  • Conveyance: Assignment
  • Assignor: Optimum Communications Services, Inc.
  • Assignee: Olio Assets L.L.C.
  • Correspondent: Not specified in the provided text.
  • Context: Transfer to an LLC.
• 2012-07-23 (executed) / recorded 2012-07-23
  • Conveyance: Assignment
  • Assignor: Optimum Communications Services, Inc.
  • Assignee: Optimum Communications Services, Inc., A Delaware Corp
  • Correspondent: Not specified in the provided text.
  • Context: Reassignment or clarification to a Delaware corporation, potentially related to the previous transfer or a change in corporate structure.
• 2016-01-22 (executed) / recorded 2016-01-22
  • Conveyance: Merger
  • Assignor: Olio Assets L.L.C.
  • Assignee: Xenogenic Development Limited Liability Company
  • Correspondent: Not specified in the provided text.
  • Context: Transfer of ownership via merger from one LLC to another.
• 2016-07-04 (executed) / recorded 2016-07-04
  • Conveyance: Assignment
  • Assignor: Optimum Communications Services, Inc.
  • Assignee: Sandstrom, Mark
  • Correspondent: Not specified in the provided text.
  • Context: Transfer back to the inventor.
• 2016-07-04 (executed) / recorded 2016-07-04
  • Conveyance: Assignment
  • Assignor: Sandstrom, Mark
  • Assignee: Optimum Communications Services, Inc., A Delaware Corporation
  • Correspondent: Not specified in the provided text.
  • Context: Immediate transfer from the inventor back to Optimum Communications Services, Inc. (Delaware Corp).

Timeline diagram

timeline
    title Ownership of US 7333511
    2002 : Filed by Optimum Comm Services Inc Canada
    2003 : Assigned to Optimum Comm Tech Inc
    2006 : Assigned to Optimum Comm Services Inc
    2008 : Patent Issued
    2012 : Reassigned to Optimum Comm Services Inc
         : Assigned to Olio Assets LLC
         : Assigned to Optimum Comm Services Inc DE
    2016 : Merged to Xenogenic Development LLC
         : Assigned to Sandstrom Mark
         : Assigned to Optimum Comm Services Inc DE

NPE / troll-pattern signals

1. Shell-entity transfer — present.
   • 2012-07-17 (executed) / recorded 2012-07-17: Assignment from Optimum Communications Services, Inc. to Olio Assets L.L.C. (an LLC).
   • 2016-01-22 (executed) / recorded 2016-01-22: Merger of Olio Assets L.L.C. into Xenogenic Development Limited Liability Company (another LLC). These transfers to LLCs are common for licensing-focused entities.
2. Known asserter in the chain — unclear. While the current assignee, Xenogenic Development LLC, is listed on Google Patents as a current assignee, it is not explicitly identified as a "known asserter" on common public NPE lists (like those from Unified Patents or RPX) in the provided information. Further research into Xenogenic Development LLC's activities would be needed.
3. Repeat correspondent across the chain — unclear. Correspondent information was not provided in the extracted patent text, making it impossible to determine if the same attorney or firm handled multiple assignments.
4. Cascading transfers — present.
   • 2012-07-17 (executed) / recorded 2012-07-17: Assignment to Olio Assets L.L.C.
   • 2012-07-23 (executed) / recorded 2012-07-23: Assignment to Optimum Communications Services, Inc., A Delaware Corporation. These two transfers occurred within 6 days, which is a strong indicator of cascading transfers.
   • 2016-07-04 (executed) / recorded 2016-07-04: Assignment to Sandstrom, Mark.
   • 2016-07-04 (executed) / recorded 2016-07-04: Assignment to Optimum Communications Services, Inc., A Delaware Corporation. These two assignments happened on the same day.
5. Pre-litigation transfer — present. Multiple litigation cases were filed in 2024, and the patent expired in July 2025. The last recorded assignments in 2016 predate the 2024 litigation by several years, but the transfers to Olio Assets LLC and Xenogenic Development LLC occurred in 2012 and 2016, respectively, which could be considered pre-litigation transfers if the original intent for assertion was established around those times. However, without knowing the exact timing of first assertion, this is a moderate signal. The litigation in 2024 (as seen in the litigation summary) is years after the last listed assignment changes, making a direct 'within 6 months' pre-litigation transfer unlikely for the initial assertion.
6. Bankruptcy fire-sale — not present. There is no indication of bankruptcy proceedings for any of the assignors in the provided information.
7. Privateering — unclear. No information in the provided text or search results suggests privateering.
8. Defensive aggregator (anti-NPE) — not present. The chain does not terminate at any known defensive aggregators.

Verdict

NPE — moderate confidence. The presence of shell-entity transfers to LLCs (Olio Assets L.L.C. and Xenogenic Development Limited Liability Company) and cascading transfers in 2012 and 2016, strongly suggests a licensing or assertion-focused strategy. Although explicit "known asserter" flags are unclear without further external database cross-references, the pattern of transfers to and between LLCs, combined with the multiple litigation cases filed in 2024, point towards an NPE model.

For verification, see the USPTO Patent Assignment Search: https://assignmentcenter.uspto.gov/

To identify the most relevant prior art for US Patent 7333511, I will access the USPTO database for the specific patent number and review its cited references.

The USPTO provides a "Patent Public Search" tool for searching U.S. patents and published applications. The provided patent text from Google Patents already includes a "Cited by" section, which lists prior art references considered during the examination of US7333511. I will use the information available within the provided patent text to identify the prior art.

Most Relevant Prior Art for US Patent 7333511

Based on the provided patent text, US Patent 7333511 cites the following patent applications as related subject matter and makes references to them in the description:

1. U.S. utility patent application Ser. No. 09/938,014

   • Full Citation: Co-pending U.S. utility patent application Ser. No. 09/938,014, filing date Aug. 24, 2001, by Mark Henrik Sandstrom, entitled “A System and Method for Maximizing the Traffic Delivery Capacity of Packet Transport Networks via Real-time Traffic Pattern Based Optimization of Transport Capacity Allocation”.
   • Publication/Filing Date: Filing date August 24, 2001.
   • Brief Description: This application provides a generic network-level method for packet traffic load adaptive allocation of transport network capacity. The current patent (US7333511) "amends" this method with specifications for an independently operating packet transport bus that enables restriction-free support for partial and spanning mesh topologies, and also provides detailed specifications for the network control signaling (bus 9 control signaling process).
   • Potential Anticipation (35 U.S.C. § 102): This reference likely describes a foundational method for traffic load-adaptive capacity allocation in packet transport networks. Given that US7333511 explicitly states it "amends" this prior application, it's highly probable that many aspects of the core concept of dynamically adjusting network capacity based on demand could be found in this earlier application. Specifically, claims related to a network system or method that involves adjusting connection capacities according to capacity demand variations, and optimizing allocation based on real-time traffic patterns (such as independent claims 1, 20, and 29) could potentially be anticipated or rendered obvious, depending on the specific novelty introduced by the "amendments" in US7333511.

2. U.S. provisional patent application Ser. No. 60/356503

   • Full Citation: U.S. provisional patent application Ser. No. 60/356503, filing date Feb. 11, 2002, by Mark Henrik Sandstrom, entitled “Real-time Control-Plane for Maximizing Billable-Traffic-Throughput of Packet Transport Networks”.
   • Publication/Filing Date: Filing date February 11, 2002.
   • Brief Description: This provisional application provides system engineering specifications for a preferred implementation of the present invention (US7333511). Specifically, Appendix B of this application, along with amendments from application, provides detailed system engineering specifications for the packet transport bus 9.
   • Potential Anticipation (35 U.S.C. § 102): As this provisional application provides "system engineering specifications for a preferred implementation" and "detailed system engineering specifications for a practical implementation of the packet transport bus 9," it likely contains significant technical details that could anticipate or render obvious specific embodiments of the claims in US7333511. Claims detailing the control plane process, the bus capacity allocation algorithm, and the structure of the control payload (e.g., portions of independent claims 1, 20, and 29, as well as dependent claims relating to these features, like claims 30-33) might find direct support in this earlier provisional application.

3. U.S. utility patent application Ser. No. 10/170,260

   • Full Citation: Co-pending U.S. utility patent application Ser. No. 10/170,260, filing date Jun. 13, 2002, by Mark Henrik Sandstrom, entitled “Input-controllable Dynamic Cross-connect”.
   • Publication/Filing Date: Filing date June 13, 2002.
   • Brief Description: This application provides a dynamic cross-connect mechanism used in a preferred implementation of a network system utilizing concepts of US7333511.
   • Potential Anticipation (35 U.S.C. § 102): While this reference describes a component used within the broader system of US7333511, the "dynamic cross-connect mechanism" itself could potentially anticipate claims relating to the specific mechanisms for reconfiguring or establishing the L1 channels. If any claims in US7333511 describe the physical or logical implementation of the channelization at a granular level that aligns with this cross-connect, those specific claims could be anticipated.

4. U.S. utility patent application Ser. No. 10/192118

   • Full Citation: Co-pending U.S. utility patent application Ser. No. 10/192118, filing date Jul. 11, 2002, by Mark Henrik Sandstrom, entitled “Transparent, Look-up-free Packet Forwarding Method for Optimizing Global Network Throughput Based on Real-time Route Status”.
   • Publication/Filing Date: Filing date July 11, 2002.
   • Brief Description: This application provides a simple, fast, and efficient packet forwarding scheme used in a preferred implementation of a network system utilizing concepts of US7333511. The network system 1 packet forwarding plane in US7333511 is said to support various forwarding features "as per the specifications in the referenced patent applications and and."
   • Potential Anticipation (35 U.S.C. § 102): This reference focuses on packet forwarding methods. Claims in US7333511 that describe aspects of packet forwarding, such as efficient packet multicasting, anycasting, dynamic traffic load balancing, route optimization, prioritization, and fast packet-level traffic protection (as mentioned in the "Bus 9 Data-Plane" section of US7333511), could be anticipated by this earlier filing, depending on the level of detail claimed in US7333511.

5. U.S. provisional patent application Ser. No. 60/400880

   • Full Citation: U.S. provisional patent application Ser. No. 60/400880, filing date Aug. 5, 2002, by Mark Henrik Sandstrom, entitled “Intelligent Transport Network Service Delivery Platform”.
   • Publication/Filing Date: Filing date August 5, 2002.
   • Brief Description: This provisional application provides amended system engineering specifications for a preferred implementation of US7333511, plus a number of practical application examples. Specifically, Appendix A of this application "amends" Appendix B of reference (Ser. No. 60/356503) to provide detailed system engineering specifications for the packet transport bus 9.
   • Potential Anticipation (35 U.S.C. § 102): Similar to provisional application Ser. No. 60/356503, this provisional application directly contributes to the "detailed system engineering specifications for a preferred practical implementation of the packet transport bus 9." Therefore, it is highly likely to contain information that could anticipate or render obvious various claims in US7333511, particularly those related to the practical implementation and specific technical details of the dynamically channelizable bus and its control plane.

6. U.S. provisional patent application Ser. No. 60/347975

   • Full Citation: U.S. provisional patent application Ser. No. 60/347975, filing date Oct. 19, 2001, by Mark Henrik Sandstrom, entitled “Intelligent Transport Network”.
   • Publication/Filing Date: Filing date October 19, 2001.
   • Brief Description: This reference provides product specifications for a practical network appliance that utilizes concepts of US7333511.
   • Potential Anticipation (35 U.S.C. § 102): As this provisional application outlines "product specifications for a practical network appliance," it would detail the practical application of the concepts underlying US7333511. Any claims in US7333511 that describe the overall network system architecture, the interaction between components, or specific functional blocks that would be part of such a network appliance (e.g., aspects of independent claims 1, 20, and 29 if they are broadly defined and could be interpreted as describing a network appliance) could potentially be anticipated.

It is important to note that all these references share the same inventor, Mark Henrik Sandstrom, and were filed before the filing date of US7333511 (August 29, 2002). This means they are highly relevant as prior art under 35 U.S.C. § 102, as they disclose inventions by the same inventive entity before the critical date of US7333511. The extent to which they anticipate or render obvious the claims of US7333511 would depend on a detailed claim-by-claim analysis against the specific disclosures in each of these earlier applications.

Obviousness Analysis of US Patent 7333511 under 35 U.S.C. § 103

This analysis assesses the obviousness of US Patent 7333511, "Dynamically channelizable packet transport network," under 35 U.S.C. § 103, by examining combinations of its own cited prior art references. A Person Having Ordinary Skill in the Art (PHOSITA) in the field of communication networks at the time of the invention (prior to August 29, 2002, the filing date of US7333511) would have been motivated to combine these references, particularly given that all share the same inventor, Mark Henrik Sandstrom, and are explicitly described in US7333511 as foundational or providing preferred implementations for the claimed invention. The goal of such combinations would be to develop a comprehensive, efficient, and high-performance packet transport network as broadly described in US7333511.

General Motivation for Combination

The inventor, Mark Henrik Sandstrom, filed all the primary prior art references before the filing date of US7333511. This strong nexus indicates that the inventor himself viewed these inventions as related and combinable elements of a broader inventive concept. US7333511 explicitly states that it "amends" earlier methods (e.g., U.S. utility application Ser. No. 09/938,014), provides "system engineering specifications for a preferred implementation" (e.g., U.S. provisional application Ser. No. 60/356503), and describes various mechanisms "used in a preferred implementation" (e.g., U.S. utility application Ser. No. 10/170,260 and U.S. utility application Ser. No. 10/192118). This explicit cross-referencing and hierarchical relationship serve as compelling motivation for a PHOSITA to combine these disclosures to achieve a complete system, as they collectively describe the architectural and operational principles for a "dynamically L1-channelizable packet transport network." The inherent motivation would be to integrate these individually disclosed components and methods to realize a full-featured, optimized packet transport network system, which is the stated objective of US7333511.

Obviousness Combinations and Rationale

The independent claims of US7333511 (Claims 1, 20, and 29) broadly cover a network system, a method for allocating bandwidth, and a process for optimizing capacity allocation, respectively, all centered on dynamically adjustable L1 connections within a packet transport bus based on real-time demand.

Combination 1: U.S. utility application Ser. No. 09/938,014 (Method) + U.S. provisional application Ser. No. 60/356503 (Control Plane) + U.S. provisional application Ser. No. 60/400880 (System Specs)

References:

• ** U.S. utility application Ser. No. 09/938,014:** Describes a "generic network level method for packet traffic load adaptive allocation of transport network capacity".
• ** U.S. provisional application Ser. No. 60/356503:** Provides "system engineering specifications for a preferred implementation" of US7333511, particularly for a "Real-time Control-Plane".
• ** U.S. provisional application Ser. No. 60/400880:** Provides "amended system engineering specifications" for a preferred implementation of US7333511 and, along with, offers "detailed system engineering specifications for a preferred practical implementation of the packet transport bus 9".

Motivation to Combine:
US7333511 explicitly states that it "amends" the method of with specifications for the independent packet transport bus and its control signaling. Furthermore, US7333511 states that Appendix B of and Appendix A of "provide detailed system engineering specifications for a preferred practical implementation of the packet transport bus 9 of the present invention". A PHOSITA would be directly motivated by these statements to combine the fundamental concept of traffic-adaptive capacity allocation from with the detailed control plane implementation from and the comprehensive system engineering specifications for the bus itself from (and) to construct a complete, operational packet transport network. The clear goal is to realize the inventor's overall system design.

Obviousness of Independent Claims (1, 20, 29):

• Claim 1 (Network System):

  • "a set of nodes including one or more source nodes and a destination node, each source node having a capacity demand figure toward the destination node": teaches traffic load adaptive allocation, inherently involving sources with demand and a destination. and would provide the specific system configurations for these nodes and the quantification of their demand figures within a network.
  • "a logical data transport bus... configured to transfer data packets from the source nodes to the destination node, the bus having an aggregate capacity that can be channelized to source node specific connections, which have an adjustable data transport capacity and each of which transports data packets from its source node to the destination node without packet-layer processing in between its source node and the destination node": US7333511 defines the "bus 9" as such a dynamically L1-channelizable bus, and states that and provide its "detailed system engineering specifications". These specifications would detail the channelization into source-specific, adjustable-bandwidth connections (e.g., using virtual concatenation of SDH/SONET paths, which are L1 and packet-layer transparent, as explicitly described in US7333511's description).
  • "digital logic at the destination node configured to allocate the aggregate capacity of the bus among its source nodes by adjusting the capacities... based at least in part on the capacity demand figures": discloses "real-time traffic pattern based optimization of transport capacity allocation". details the "real-time control plane" that would embody this "digital logic" at the destination node (egress interface) to perform the allocation and capacity adjustment, further refined by.

• Claim 20 (Method for Allocating Bandwidth):

  • "allocating, by the destination of the bus, said total bus bandwidth among said individual sources based at least in part on the traffic loads...": This core allocation step is taught by's "traffic pattern based optimization of transport capacity allocation" and fully elaborated within the "real-time control plane" context of and, which describes the destination (egress interface) as responsible for this allocation.
  • "assigning, by the destination of the bus, units of bus bandwidth for the source-specific channels on the bus according to the allocating of the bus bandwidth": This is a direct consequence of the allocation, specifying the granular implementation of bandwidth. The "detailed system engineering specifications" of and would necessarily cover the assignment of these "units" (e.g., STS-1 or VC-3 slots, as explained in US7333511).
  • "transporting data packets over the bus from the source nodes to the destination node based on the assigning of units of bus bandwidth for the source-specific channels": This describes the functional outcome of the system, where the bus, as specified in and, transports packets via the established channels.

• Claim 29 (Process for Optimizing Capacity Allocation):

  • "optimizing, by the egress interface, allocation of said capacity pool among the individual ingress interfaces for transport of data packets... based at least in part on demand for network capacity": This optimization is a direct teaching of's "traffic pattern based optimization" and is implemented by the "real-time control plane" detailed in and, where the egress interface (destination node) performs this function based on demand.
  • "assigning, by the egress interface, units of capacity within said capacity pool to said individual ingress interfaces according to the optimizing of capacity allocation": This step naturally follows the optimization and forms part of the system engineering detailed in and for the control plane.
  • "transporting data packets from the ingress interfaces nodes to the egress interface based on the assigning of units of capacity within said capacity pool": This describes the fundamental operation of the network system, enabled by the dynamically channelized bus described in and.

Combination 2: Combination 1 + U.S. utility application Ser. No. 10/170,260 (Dynamic Cross-connect) + U.S. utility application Ser. No. 10/192118 (Packet Forwarding)

Additional References:

• ** U.S. utility application Ser. No. 10/170,260:** Provides a "dynamic cross-connect mechanism used in a preferred implementation" of a network system utilizing concepts of US7333511.
• ** U.S. utility application Ser. No. 10/192118:** Provides a "simple, fast and efficient packet forwarding scheme used in a preferred implementation" of a network system utilizing concepts of US7333511.

Motivation to Combine:
US7333511 explicitly states that and describe mechanisms "used in a preferred implementation of a network system 1 utilizing concepts of the present invention". A PHOSITA, aiming to build a practical and highly efficient network system as envisioned by the inventor, would naturally integrate the core capacity allocation and control plane (from Combination 1) with specific, known solutions for dynamically forming L1 channels (using the cross-connect of) and for efficiently handling packets once those channels are established (using the forwarding scheme of). The motivation is to move from a conceptual and specification level to a concrete, optimized, and fully functional system.

Obviousness of Independent Claims (1, 20, 29):
This combination further strengthens the obviousness arguments by providing specific technical means for implementing various aspects of the claims:

• Claim 1 (Network System):

  • The "adjustable data transport capacity" of the L1 source node specific connections, and the "digital logic... adjusting the capacities," would be concretely implemented by the input-controllable dynamic cross-connect of. This cross-connect provides the mechanism to dynamically reconfigure the L1 channels.
  • The overall functionality of the "network system" in handling data packets would incorporate the "transparent, look-up-free packet forwarding method" described in.

• Claim 20 (Method for Allocating Bandwidth):

  • The "assigning... units of bus bandwidth for the source-specific channels" would leverage the dynamic cross-connect mechanism of to physically or logically establish these channels based on the allocation.
  • The "transporting data packets over the bus" would then be efficiently managed by the packet forwarding method of.

• Claim 29 (Process for Optimizing Capacity Allocation):

  • The "assigning... units of capacity within said capacity pool" by the egress interface would utilize the dynamic cross-connect mechanism of to realize the channel assignments at Layer 1.
  • The subsequent "transporting data packets" from ingress to egress would employ the efficient packet forwarding scheme of.

Conclusion on Obviousness

Considering the explicit cross-references within US7333511 to the inventor's own prior art, and the descriptions of these references as providing foundational methods, detailed specifications, or preferred implementations, a PHOSITA would have been highly motivated to combine these disclosures. The combination of U.S. utility application Ser. No. 09/938,014 (for the adaptive allocation method), U.S. provisional application Ser. No. 60/356503 (for the control plane specifications), and U.S. provisional application Ser. No. 60/400880 (for the detailed bus system specifications) would render the core concepts of the network system (Claim 1), the method for allocating bandwidth (Claim 20), and the process for optimizing capacity allocation (Claim 29) obvious. Further integration of U.S. utility application Ser. No. 10/170,260 (for dynamic cross-connects) and U.S. utility application Ser. No. 10/192118 (for packet forwarding) would render specific implementations of channel adjustment and packet handling obvious, as they represent specific solutions for elements explicitly called for in a "preferred embodiment" of the claimed invention.

The results of these combinations would be predictable, achieving precisely the functionalities described in US7333511, such as dynamic L1 channelization and real-time traffic-adaptive capacity allocation, to maximize network throughput for packet traffic. The fact that the inventor himself authored all these preceding applications further underscores the obviousness of combining them to create the system described and claimed in US7333511.

To provide a detailed analysis of US Patent 7333511 regarding patent term adjustments (PTA), patent term extensions (PTE), continuation applications, divisional applications, related family members, and the projected expiration date, information from the USPTO's official patent records for this specific patent would be required. While the provided patent text from Google Patents offers some details, a direct query to the USPTO's Patent Center or Public Search databases is necessary for the most accurate and complete information, especially for PTA/PTE calculations and family relationships beyond what's explicitly stated in the patent's descriptive text.

Based on the information available and general patent law principles:

Patent Term Adjustments (PTA)

Patent Term Adjustment (PTA) can add time to a patent's 20-year term to compensate for delays caused by the USPTO during the patent examination process. These delays fall into categories such as:

• A-Delay: USPTO failing to issue a first Office Action within 14 months of filing, or responding to applicant replies or appeals within 4 months, or issuing the patent within 4 months after issue fee payment.
• B-Delay: The application remaining pending for more than three years.
• C-Delay: Delays due to interferences, secrecy orders, or successful appeals.

Any applicant-caused delays (e.g., taking longer than three months to reply to an Office Action) would reduce the PTA. The exact PTA for US7333511 would be calculated by the USPTO at the time of patent issuance and would be included in the Issue Notification Letter. Without access to the specific prosecution history and issue notification for US7333511 from the USPTO database, the precise PTA cannot be determined.

Patent Term Extensions (PTE)

Patent Term Extensions (PTE) are available for patents claiming certain human drug products, medical device products, animal drug products, veterinary biological products, and food or color additive products, to restore time lost during premarket government approval from a regulatory agency (e.g., FDA).

• US Patent 7333511 relates to "dynamically channelizable packet transport networks" and "communications networks," which does not fall into the categories of products eligible for PTE. Therefore, it is highly unlikely that US7333511 would have received any Patent Term Extensions.

Continuation Applications

A continuation application is a patent application filed by an applicant to pursue additional claims to an invention disclosed in an earlier, still-pending parent application. It uses the same specification as the parent and claims the priority based on the parent's filing date.

• To determine if US7333511 is a continuation of an earlier application, or if it has any continuation applications flowing from it, a review of the "Related U.S. Application Data" section within the patent document or its prosecution history on the USPTO website would be necessary. The provided patent text does not explicitly state that US7333511 is a continuation of another application, other than its claims of benefit to provisional applications and referencing related utility applications. The related utility applications listed are:
  • U.S. utility patent application Ser. No. 09/938,014, filed Aug. 24, 2001.
  • U.S. utility patent application Ser. No. 10/170,260, filed Jun. 13, 2002.
  • U.S. utility patent application Ser. No. 10/192118, filed Jul. 11, 2002.
    These applications share the same inventor and are related subject matter, but without official USPTO family data, it cannot be definitively stated if they are formal continuation applications in the legal sense or simply related disclosures.

Divisional Applications

A divisional application is a type of continuing application filed when the USPTO requires an applicant to restrict their original application to one invention, allowing the applicant to pursue other disclosed but unclaimed inventions in separate applications. A divisional application is entitled to the filing date of the original application.

• Similar to continuation applications, the existence of any divisional applications for US7333511 would be indicated in its "Related U.S. Application Data" section or prosecution history. The provided patent text does not explicitly mention any divisional applications.

Related Family Members

A patent family is a group of patent applications and patents with interrelating priority claims, covering related inventions or features. The "Related U.S. Application Data" section in the patent document explicitly lists U.S. provisional applications for which US7333511 claims benefit under 35 U.S.C. § 119(e):

• U.S. provisional patent application Ser. No. 60/356503, filed Feb. 11, 2002.
• U.S. provisional patent application Ser. No. 60/400880, filed Aug. 5, 2002.
  These provisional applications are considered family members, establishing an earlier priority date for the subject matter disclosed within them. The other utility applications mentioned in the cross-references are also related, as discussed above.

Projected Expiration Date

The standard term for a U.S. utility patent filed on or after June 8, 1995, is 20 years from the earliest effective filing date of the application.

• The filing date of US Patent 7333511 is August 29, 2002.
• The patent claims priority to provisional applications, with the earliest priority date being October 19, 2001, from U.S. provisional patent application Ser. No. 60/347975 (though only 60/356503 and 60/400880 are explicitly claimed for benefit under 35 U.S.C. § 119(e) in the patent's cross-references).
• However, provisional application filing dates are generally not used to calculate the 20-year patent term. The 20-year term typically starts from the earliest non-provisional filing date to which the patent claims priority.
• The earliest non-provisional filing date listed in the patent's references, by the same inventor, is August 24, 2001, for U.S. utility patent application Ser. No. 09/938,014. If US7333511 claims priority to this utility application under 35 U.S.C. § 120, then the 20-year term would begin from August 24, 2001.
• The provided Google Patents information states the legal status as "Expired - Lifetime" with an expiration date of July 30, 2025. This "Adjusted expiration" date likely already incorporates any PTA.
• Without access to the official USPTO patent term calculator output or a definitive statement from the USPTO regarding PTA and specific priority chain for US7333511, a precise calculation of the projected expiration date beyond what Google Patents provides is not possible. However, based on the Google Patents information, the patent has already expired on July 30, 2025.

Defensive Disclosure for US Patent 7333511: Dynamically Channelizable Packet Transport Network

Publication Date: 2026-07-21

Inventor(s): Mark Henrik Sandstrom
Assignee(s) (Current): Optimum Communications Services Inc, A Delaware Corp; Mark Sandstrom; Xenogenic Development LLC
Related Patent: US 7333511 B2

This defensive disclosure aims to broaden the scope of publicly available prior art related to dynamically channelizable packet transport networks, building upon the foundational concepts of US Patent 7333511. The objective is to render future incremental improvements or variations in this technological domain obvious or non-novel to a Person Having Ordinary Skill in the Art (PHOSITA) by presenting a series of derivative works that extend the core claims of US7333511 across various technical axes.

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Derivatives of Independent Claim 1: Network System

Claim 1: A network system for maximizing its data throughput by adjusting its connection capacities according to their capacity demand variations, the network system comprising: a set of nodes including one or more source nodes and a destination node, each source node having a capacity demand figure toward the destination node, a logical data transport bus, referred to as a bus, configured to transfer data packets from the source nodes to the destination node, the bus having an aggregate capacity that can be channelized to source node specific connections, which have an adjustable data transport capacity and each of which transports data packets from its source node to the destination node without packet-layer processing in between its source node and the destination node, and digital logic at the destination node configured to allocate the aggregate capacity of the bus among its source nodes by adjusting the capacities of the source node specific connections on the bus at least in part based on the capacity demand figures from the source nodes toward the destination node of the network system.

---

Derivative 1.1: Material & Component Substitution - All-Optical Terahertz Bus

Enabling Description:
This derivative envisions a network system where the "logical data transport bus" and its "source node specific connections" are implemented entirely using all-optical components operating in the terahertz (THz) frequency range. Instead of SDH/SONET virtual concatenation of electrical or optical signals, the capacity allocation units are dynamically configurable THz wavelength channels or time-domain multiplexed THz pulses. The nodes are replaced with all-optical packet switching elements, such as those employing plasmonic modulators or resonant tunneling diodes for ultrafast optical processing. Demand figures are collected via integrated optical sensors at the source nodes, measuring optical buffer occupancy. The "digital logic at the destination node" is implemented using a dedicated optical processor (e.g., based on optical computing architectures or reconfigurable photonic integrated circuits) capable of real-time THz channel allocation by tuning optical cross-connects (e.g., MEMS-based optical switches, liquid crystal switches, or lithium niobate modulators) to establish source-specific THz channels. Packet-layer transparency is maintained by encoding data directly into THz pulse characteristics (e.g., amplitude, phase, or polarization modulation) without opto-electronic conversion within the L1 channel path.

graph TD
    A[Source Node 1 (Optical Buffer)] -- THz Demand Signal --> D(Optical Processor / Digital Logic)
    B[Source Node N (Optical Buffer)] -- THz Demand Signal --> D
    D -- THz Channel Allocation (Optical Control) --> E(All-Optical THz Bus)
    E -- THz Data Channel 1 --> C[Destination Node (Optical Demux)]
    E -- THz Data Channel N --> C
    D -- THz Channel Configuration --> E

---

Derivative 1.2: Operational Parameter Expansion - Nanoscale Inter-Chip Bus

Enabling Description:
This derivative applies the dynamic channelization concept to an inter-chip communication fabric within a multi-chip module (MCM) or a chiplet-based system, operating at nanoscale dimensions and ultra-high frequencies (e.g., hundreds of GHz to THz range). The "nodes" are individual chiplets or functional blocks within a System-on-Chip (SoC). The "logical data transport bus" is realized as a nanoscale photonic interconnect (e.g., silicon photonics waveguides, plasmonic waveguides, or carbon nanotube bundles configured for high-frequency electrical signaling). The "capacity allocation units" are fine-grained wavelength channels (WDM) or specific time slots (TDM) within the nanoscale interconnect. "Demand figures" are represented by buffer occupancy within the transmitting chiplet's network-on-chip (NoC) interface logic, communicated via dedicated low-latency control channels (e.g., electrical sidebands or separate control wavelengths). The "digital logic at the destination node" is implemented as a dedicated hardware acceleration block (e.g., a reconfigurable array of logic gates or a specialized ASIC) responsible for dynamic allocation of waveguide segments or wavelength groups to individual source chiplets. This allows for real-time traffic-adaptive bandwidth allocation between processing units on a single board or within a single package, optimizing inter-chiplet data flow without high-overhead packet-layer processing.

graph TD
    A[Chiplet 1 (NoC Interface & Buffer)] -- Buffer Occupancy (Control Wavelength) --> D(Hardware Allocation Logic)
    B[Chiplet N (NoC Interface & Buffer)] -- Buffer Occupancy (Control Wavelength) --> D
    D -- WDM/TDM Channel Config --> E(Nanoscale Photonic Interconnect Bus)
    E -- Data Channel 1 --> C[Destination Chiplet (NoC Interface)]
    E -- Data Channel N --> C

---

Derivative 1.3: Cross-Domain Application - Smart Grid Energy Distribution Network

Enabling Description (Smart Grid):
In a smart grid context, the "nodes" are smart meters, substations, distributed energy resources (DERs), and utility control centers. The "logical data transport bus" is a virtual communication channel overlayed on existing power line communication (PLC) infrastructure, fiber optic networks, or wireless mesh networks, responsible for transmitting critical grid state data (e.g., voltage, current, frequency, DER output) from source components (e.g., smart meters, DERs) to a destination (e.g., a regional control center). The "aggregate capacity" is the total available bandwidth for real-time grid telemetry. "Source node specific connections" are dynamically allocated segments of bandwidth for specific data streams. "Capacity demand figures" are derived from the urgency and volume of data generated by grid events (e.g., fault detection, sudden load changes, renewable energy fluctuations). The "digital logic at the destination node" (e.g., at the control center's data acquisition system) dynamically adjusts the communication bandwidth allocated to each source based on its priority (e.g., fault data vs. routine meter readings) and current demand, ensuring low-latency transport of critical control and telemetry information to prevent grid instabilities or blackouts. This operates at a Layer 1 perspective by carving out raw bandwidth, transparent to the SCADA or other application-layer protocols.

graph TD
    A[Smart Meter / DER 1] -- Grid Data Stream --> E(Smart Grid Comm Bus)
    B[Substation N] -- Grid Data Stream --> E
    E -- Control Signals --> C[Control Center (Data Acquisition)]
    C -- Bandwidth Allocation Policy --> E
    A -- Data Urgency/Volume (Demand) --> C
    B -- Data Urgency/Volume (Demand) --> C

---

Derivative 1.4: Cross-Domain Application - Autonomous Vehicle Sensor Fusion Backbone

Enabling Description (Autonomous Vehicles):
For an autonomous vehicle, the "nodes" are various sensors (e.g., LiDAR, radar, cameras, ultrasonic), ECUs (Electronic Control Units) for specific functions (e.g., perception, planning, control), and the central processing unit (CPU)/GPU complex. The "logical data transport bus" is an in-vehicle high-speed communication backbone (e.g., Automotive Ethernet, PCIe over optical fiber, or custom high-speed serial links) that transports raw and pre-processed sensor data to the central processing complex. The "aggregate capacity" is the total bandwidth of this backbone. "Source node specific connections" are dynamically carved L1 channels for individual sensor data streams. "Capacity demand figures" are real-time data rates from sensors, influenced by environmental conditions (e.g., heavy rain increasing camera data, dense traffic increasing radar returns) or operational modes (e.g., high-speed highway driving requiring higher LiDAR resolution). The "digital logic at the destination node" (e.g., an intelligent network interface card (NIC) within the central CPU/GPU complex) dynamically adjusts the L1 bandwidth allocated to each sensor stream to ensure critical data (e.g., objects in immediate path) receive guaranteed low-latency transport, optimizing sensor data flow for real-time decision-making without adding packet processing overhead on the backbone itself.

graph TD
    A[LiDAR Sensor] -- Raw Data Stream --> E(In-Vehicle Comm Backbone)
    B[Radar Sensor] -- Raw Data Stream --> E
    E -- Sensor Data Channel --> C[Central CPU/GPU (Sensor Fusion)]
    C -- Bandwidth Control --> E
    A -- Data Rate/Priority (Demand) --> C
    B -- Data Rate/Priority (Demand) --> C

---

Derivative 1.5: Cross-Domain Application - Industrial IoT Predictive Maintenance Network

Enabling Description (Industrial IoT):
In an Industrial IoT (IIoT) environment for predictive maintenance, the "nodes" are machinery with embedded sensors (e.g., vibration, temperature, acoustic), edge gateways, and a central plant monitoring system. The "logical data transport bus" is a dedicated, low-latency industrial communication network (e.g., TSN Ethernet, optical fiber, or dedicated wireless channels like 5G URLLC slicing) transporting machine health data. The "aggregate capacity" is the total available bandwidth for IIoT data. "Source node specific connections" are dynamically allocated L1 channels for specific machine sensor groups or edge gateways. "Capacity demand figures" are triggered by anomaly detection at the edge (e.g., vibration signature exceeding thresholds, indicating imminent failure) or by periodic high-resolution data dumps for analysis. The "digital logic at the destination node" (e.g., within the plant monitoring system's data ingestion layer) prioritizes and allocates bandwidth to data streams from machines showing early signs of failure, ensuring that critical diagnostic data reaches the central system with minimal delay, enabling proactive maintenance actions. The L1 nature ensures deterministic performance for critical machine-to-machine or machine-to-controller communications.

graph TD
    A[Machine 1 (Vibration Sensor)] -- Health Data Stream --> E(Industrial Comm Network)
    B[Edge Gateway N (Anomaly Detection)] -- Aggregated Data --> E
    E -- Machine Health Channel --> C[Plant Monitoring System]
    C -- Bandwidth Control --> E
    A -- Anomaly Flag/Data Burst (Demand) --> C
    B -- Anomaly Flag/Data Burst (Demand) --> C

---

Derivative 1.6: Integration with Emerging Tech - AI-Driven, IoT-Enhanced, Blockchain-Verified Network

Enabling Description:
This derivative enhances the network system of Claim 1 by integrating AI for predictive capacity demand, IoT sensors for granular L1 channel monitoring, and blockchain for verifiable allocation.

• AI-Driven Optimization: The "digital logic at the destination node" (or an augmented control plane) is an AI agent (e.g., a Reinforcement Learning model) that not only reacts to current "capacity demand figures" but predicts future traffic load patterns from source nodes. IoT sensors (e.g., optical power meters, buffer occupancy monitors, packet loss counters) embedded within the network interfaces of the source nodes and along the L1 bus itself provide real-time telemetry (latency, jitter, bandwidth utilization) to the AI agent. The AI continuously optimizes the "capacity allocation pattern" to maximize global throughput and minimize latency, preemptively adjusting "source node specific connections" based on predicted demand rather than just reactive measurements.
• IoT Sensors for Real-time Monitoring: Each "source node" and key points along the "logical data transport bus" are equipped with miniaturized IoT sensors that capture precise L1 metrics (e.g., optical signal-to-noise ratio, frame error rates, micro-burst detection). This telemetry is fed into the AI optimization engine to refine its predictive models and validate allocation effectiveness.
• Blockchain for Supply Chain Verification / Allocation Audit: The "capacity allocation info" (e.g., the virtual concatenation coefficients) and the "capacity demand figures" are recorded as transactions on a permissioned blockchain (e.g., Hyperledger Fabric). Each allocation decision by the "digital logic" (AI agent) is timestamped and immutably stored. This provides an auditable, tamper-proof log of bandwidth provisioning, ensuring fairness, accountability, and enabling service level agreement (SLA) verification across different network slices or tenant traffic, especially in multi-domain or multi-provider scenarios.

sequenceDiagram
    participant S1 as Source Node 1 (w/ IoT)
    participant SN as Source Node N (w/ IoT)
    participant D as Destination Node (w/ AI Logic)
    participant B as Blockchain Ledger
    participant OPM as Optical Power Meters (IoT)

    loop Every Control Cycle (e.g., 1ms)
        S1->>D: Real-time Demand Figures (Traffic Load, Buffer)
        SN->>D: Real-time Demand Figures (Traffic Load, Buffer)
        OPM->>D: L1 Telemetry (Latency, Util.)
        D->>D: AI Predicts Future Demand & Optimizes Allocation
        D->>D: Generates Capacity Allocation Info
        D->>E: Adjust L1 Channels (VC Coefficients)
        E->>S1: Transport Data on Ch1
        E->>SN: Transport Data on ChN
        D->>B: Record Allocation Decision & Telemetry
        B-->>D: Acknowledge Transaction
    end

---

Derivative 1.7: The "Inverse" or Failure Mode - Graceful Degradation Bus with Minimum Viable Channels

Enabling Description:
This derivative focuses on a version of the network system designed for graceful degradation under adverse conditions, such as major link failures or power outages, while ensuring a minimum viable communication capability. The "logical data transport bus" includes a pre-provisioned set of "minimum viable channels" (MVCs) at L1. These MVCs are the lowest possible bandwidth units (e e.g., single STS-1 or VC-3 paths, or even sub-rate channels if applicable), reserved for emergency signaling or essential low-bandwidth data. In a failure scenario (detected by network monitoring, e.g., loss of pilot tones, persistent CRC errors), the "digital logic at the destination node" (or an embedded hardware state machine) switches from throughput-maximizing allocation to a "failure mode" where all aggregate capacity not already failed is immediately reallocated to guarantee the MVCs for critical source nodes (e.g., emergency services, control plane signaling). Remaining capacity, if any, is then distributed in a round-robin or strict-priority fashion to non-critical traffic, overriding normal demand-based optimization. This system is designed to "fail safely" by ensuring essential communication paths remain operational as long as any L1 connectivity exists, albeit at reduced performance. A "low-power" mode could dynamically reduce the total aggregate bus capacity by deactivating unused high-speed transponders and re-optimizing allocation over a smaller, power-efficient subset of L1 resources.

stateDiagram
    [*] --> Normal_Operation
    Normal_Operation --> Failure_Detected: Link_Loss | High_Error_Rate
    Failure_Detected --> Graceful_Degradation: Activate_Failure_Mode
    Graceful_Degradation --> Minimum_Viable_Channels_Active: Prioritize_MVCs
    Minimum_Viable_Channels_Active --> Reduced_Functionality_Traffic: Allocate_Remaining_Capacity
    Graceful_Degradation --> Low_Power_Mode: Power_Saving_Directive
    Low_Power_Mode --> Normal_Operation: Restore_Power | Link_Restored
    Reduced_Functionality_Traffic --> Normal_Operation: Link_Restored | Repair_Complete
    Minimum_Viable_Channels_Active --> Normal_Operation: Link_Restored | Repair_Complete
    Normal_Operation --> [*]

---

Derivatives of Independent Claim 20: Method for Allocating Bandwidth

Claim 20: A method for allocating a total data transport bandwidth on a data packet transport bus referred to as a bus, said bus having two or more data sources and a destination, said bus further providing source-specific variable-bandwidth channels from the individual sources of the bus to the destination of the bus for transporting data packets from the individual sources to the destination of the bus, the sources of the bus having their associated data traffic loads toward the destination of the bus, the method executed periodically once per a period of time referred to as an algorithm period, the method comprising: allocating, by the destination of the bus, said total bus bandwidth among said individual sources based at least in part on the traffic loads associated with the individual sources of the bus, assigning, by the destination of the bus, units of bus bandwidth for the source-specific channels on the bus according to the allocating of the bus bandwidth, and transporting data packets over the bus from the source nodes to the destination node based on the assigning of units of bus bandwidth for the source-specific channels.

---

Derivative 2.1: Material & Component Substitution - Quantum Entanglement Channel Allocation

Enabling Description:
This derivative reimagines the "bus" as a quantum entanglement-based communication channel, where "units of bus bandwidth" are defined by the rate of entangled qubit pairs shared between source and destination nodes, potentially enabling secure, high-speed L1 channels. The "sources" and "destination" are equipped with quantum processors and entanglement distribution modules. The "traffic loads" are quantified by the computational load and data volume to be transmitted quantum mechanically or classically over quantum-secured links. The "allocating" step involves the destination coordinating the rate of entanglement generation or distribution with each source, effectively defining the L1 channel capacity. The "assigning" step corresponds to dynamically adjusting the quantum key distribution (QKD) rate or the rate of entangled state transmission to each source, establishing a variable-bandwidth, quantum-layer transparent channel. "Transporting data packets" would then occur either via quantum teleportation (for quantum data) or classical data encrypted with keys derived from the dynamically allocated QKD channels. This operates at a fundamental physical layer, even below traditional L1, by directly managing a quantum resource.

sequenceDiagram
    participant S1 as Quantum Source Node 1
    participant SN as Quantum Source Node N
    participant D as Quantum Destination Node
    participant EQN as Entanglement Generation Network

    loop Algorithm Period
        S1->>D: Classical Demand Signal (Qubit-pair Rate)
        SN->>D: Classical Demand Signal (Qubit-pair Rate)
        D->>D: Allocate Entanglement Rate Based on Demand
        D->>EQN: Request Entanglement Distribution Rate for S1
        D->>EQN: Request Entanglement Distribution Rate for SN
        EQN-->>S1: Establish Entangled Qubit-Pair Rate for Channel 1
        EQN-->>SN: Establish Entangled Qubit-Pair Rate for Channel N
        S1->>D: Transport Data (Quantum or QKD-Secured Classical)
        SN->>D: Transport Data (Quantum or QKD-Secured Classical)
    end

---

Derivative 2.2: Operational Parameter Expansion - Hyperspectral Multi-Wavelength Optical Bus

Enabling Description:
This method extends the current SDH/SONET/WDM approach to a "hyperspectral" optical bus, utilizing an extremely dense array of narrow-band optical carriers across a broad spectrum (e.g., C+L+S bands, or even beyond into mid-infrared). The "total bus bandwidth" is the aggregate capacity of thousands of tightly packed wavelength channels. The "units of bus bandwidth" are individual wavelength channels, each with a fractional capacity of a standard SDH/SONET container (e.g., 1/10th of an STS-1 equivalent). The "allocating" step by the destination involves assigning specific, non-contiguous wavelength channels to individual sources. This requires advanced tunable lasers and receivers at each node, capable of locking onto a dynamic set of discrete wavelengths. The "assigning" step uses active optical switching (e.g., fast tunable filters, MEMS-based wavelength selective switches) to reconfigure these channels at sub-millisecond "algorithm periods." "Transporting data packets" is then performed over these highly granular, dynamically assigned hyperspectral L1 channels, enabling extremely fine-grained, adaptive bandwidth allocation for ultra-dense WDM systems.

graph LR
    S1[Source 1: Tunable Laser/Rx] -- Demand --> D(Destination: Optical Controller)
    SN[Source N: Tunable Laser/Rx] -- Demand --> D
    D -- Wavelength Allocation --> OWB[Optical Wavelength Bus (Hyperspectral)]
    OWB -- Data --> S1
    OWB -- Data --> SN
    D -- Wavelength Assignment --> S1
    D -- Wavelength Assignment --> SN

---

Derivative 2.3: Cross-Domain Application - Smart City Public Safety Communications

Enabling Description (Smart City Public Safety):
In a smart city, the "bus" is a public safety communication backbone shared by various emergency services (police, fire, EMS, traffic control). The "sources" are individual first responders, mobile command centers, city-wide sensor networks (e.g., traffic cameras, gunshot detectors), and IoT devices deployed for public safety. The "destination" is a central emergency operations center (EOC). "Traffic loads" correspond to real-time data from incident scenes (e.g., body camera feeds, drone footage, sensor data on environmental hazards), voice communications, and resource coordination data. The "method for allocating" involves the EOC dynamically assigning high-priority, dedicated L1 communication channels (e.g., using 5G network slicing or dedicated CBRS channels configured as virtual point-to-point links) to specific incident commanders or critical sensor feeds based on the severity and scale of an emergency. This ensures guaranteed bandwidth and minimal latency for vital public safety communications, even during peak network congestion, overriding non-critical traffic.

flowchart TD
    subgraph Emergency Services
        A[First Responder (Body Cam)]
        B[Mobile Command Center]
        C[Smart City Sensor Network]
    end

    A -- Data/Voice Stream --> Bus(Public Safety Comm Bus)
    B -- Data/Voice Stream --> Bus
    C -- Data/Voice Stream --> Bus

    Bus --> EOC(Emergency Operations Center)
    EOC -- Demand/Priority --> D[Control Logic]
    D -- Allocate Bandwidth (L1 Slice) --> Bus
    EOC -- Assign Channels (L1 Slice) --> Bus
    Bus -- Transport Data --> EOC

---

Derivative 2.4: Cross-Domain Application - High-Frequency Trading Market Data Distribution

Enabling Description (High-Frequency Trading):
In a high-frequency trading (HFT) environment, the "bus" is a ultra-low-latency dedicated fiber link carrying market data feeds. The "sources" are individual exchanges or market data providers. The "destination" is an HFT firm's trading engine cluster. "Traffic loads" are real-time order book updates, trade executions, and quotes from various markets. The "method for allocating" involves the trading engine's ingress network interface controller (NIC) or a dedicated front-end processing unit dynamically allocating raw L1 fiber capacity (e.g., using wavelength or time-slot allocation within a DWDM link) to specific market data feeds. "Demand" is determined by the volatility of a market or the importance of a particular asset class. The "assigning" step ensures that the highest-priority, most volatile market data streams receive dedicated, unbuffered L1 paths, minimizing jitter and latency to gain a competitive edge in trade execution. This is transparent to upper-layer financial protocols (e.g., FIX, ITCH).

graph TD
    A[Exchange A (Order Book)] -- Market Data Stream --> E(Ultra-Low-Latency Fiber Bus)
    B[Exchange N (Quotes)] -- Market Data Stream --> E
    E -- Data Channel --> C[Trading Engine Cluster]
    C -- Bandwidth Allocation --> E
    A -- Volatility/Priority (Demand) --> C
    B -- Volatility/Priority (Demand) --> C

---

Derivative 2.5: Integration with Emerging Tech - Dynamic L1 Bus with SDN Control and Open-Source Protocols

Enabling Description:
This method integrates the dynamic L1 channelization with Software-Defined Networking (SDN) principles, leveraging open-source protocols for centralized control and distributed enforcement.

• SDN Control Plane: A central SDN controller (e.g., Open Daylight, ONOS) acts as the "destination of the bus" for control purposes. It receives "traffic loads" (capacity demand figures) from source nodes via OpenFlow or NETCONF/YANG telemetry.
• AI-Powered Optimization: Within the SDN controller, an AI module (e.g., using deep reinforcement learning) performs the "allocating" step, determining the optimal L1 channel configurations (e.g., VC-n-Xv coefficients) across the underlying SDH/SONET/WDM infrastructure based on real-time and predicted demands, QoS policies, and network conditions.
• OpenFlow/NETCONF Enforcement: The "assigning" step involves the SDN controller pushing configuration changes (e.g., cross-connect mappings for VC-n paths, wavelength assignments for WDM) to programmable L1 network elements (e.g., ROADMs, digital cross-connects) using OpenFlow, NETCONF, or a custom L1 control protocol.
• Data Plane Enforcement: The actual "transporting data packets" uses the reconfigured L1 channels. The source nodes continue to encapsulate packets (e.g., MPLS, Ethernet) over these virtual concatenated L1 paths. The entire process cycle is orchestrated by the SDN controller, enabling dynamic, global optimization of L1 resources.

sequenceDiagram
    participant S as Source Node
    participant L1_NE as L1 Network Element (e.g., ROADM)
    participant D as Destination Node
    participant SDN_C as SDN Controller (w/ AI)

    loop Algorithm Period
        S->>L1_NE: Data Stream (Encapsulated)
        L1_NE->>D: Data Stream (Encapsulated)
        S->>SDN_C: Traffic Load/Demand (OpenFlow/Telemetry)
        SDN_C->>SDN_C: AI Allocates L1 Bandwidth
        SDN_C->>L1_NE: Assign L1 Channels (OpenFlow/NETCONF)
        L1_NE->>L1_NE: Reconfigure Cross-Connects/Wavelengths
        L1_NE->>D: Transport Data over New L1 Channels
    end

---

Derivative 2.6: The "Inverse" or Failure Mode - Cost-Optimized, Shared-Resource Bandwidth Allocation

Enabling Description:
This method prioritizes cost-efficiency and resource sharing over guaranteed throughput, operating in an "inverse" fashion to the patent's primary objective of maximizing throughput. The "allocating" step by the destination aims to minimize the number of activated L1 capacity units while still satisfying a minimum guaranteed service level for each source. Instead of continuously maximizing throughput by fully utilizing the bus, the algorithm dynamically identifies opportunities to deallocate L1 capacity units and put them into a shared pool or even power-saving sleep states if traffic loads decrease below a threshold. "Fairness" is redefined not as equal share of excess bandwidth, but as equal opportunity to access shared idle capacity when needed, after minimums are met. The "algorithm period" might be longer to reduce control overhead. When demand increases, the system dynamically "awakens" additional L1 capacity units from the shared pool. "Transporting data packets" would then occur over these more sparsely allocated, shared-resource L1 channels, which might incur slightly higher initial latency as channels are provisioned but offer significant operational cost savings (e.g., reduced power consumption, extended equipment lifespan).

graph TD
    S1[Source 1: Low Priority] -- Demand --> D(Destination: Cost-Optimizer Logic)
    S2[Source 2: High Priority] -- Demand --> D
    D -- Allocation Policy (Min Cost, Min QoS) --> Bus[Logical Data Transport Bus]
    Bus -- Data Traffic --> S1
    Bus -- Data Traffic --> S2
    D -- Deallocate / Allocate --> Shared_Pool(Shared L1 Capacity Pool)
    Shared_Pool -- Re-allocate on Demand --> Bus

---

Derivatives of Independent Claim 29: Process for Optimizing Capacity Allocation

Claim 29: A process for optimizing capacity allocation within a data transport network system referred to as a network system, the network system comprising a set of ingress interfaces, an egress interface, and a capacity pool for transporting data packets from the set of ingress interfaces to the egress interface of the network system, the process having a repeating process cycle, each process cycle comprising the steps: optimizing, by the egress interface, allocation of said capacity pool among the individual ingress interfaces for transport of data packets from the ingress interfaces to the egress interface based at least in part on demand for network capacity by the individual ingress interfaces for transporting data from them to the egress interface of the network system, assigning, by the egress interface, units of capacity within said capacity pool to said individual ingress interfaces according to the optimizing of capacity allocation, and transporting data packets from the ingress interfaces nodes to the egress interface based on the assigning of units of capacity within said capacity pool.

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Derivative 3.1: Material & Component Substitution - Metamaterial-Based Radio Frequency (RF) Bus

Enabling Description:
This derivative implements the "data transport network system" as a metamaterial-based radio frequency (RF) bus within a constrained physical space (e.g., a data center rack or avionics system), where electromagnetic waves are guided and shaped by engineered metamaterials. The "ingress interfaces" and "egress interface" are compact metamaterial antennas coupled to transceivers. The "capacity pool" is the available spectrum within the RF bus, which can be dynamically sliced into sub-bands or specific spatial modes. "Units of capacity" are frequency bands or orthogonal spatial channels. The "optimizing" and "assigning" steps are performed by a reconfigurable metamaterial controller at the "egress interface." This controller uses electrical or optical signals to actively reconfigure the metamaterial properties (e.g., reflectivity, refractivity, polarization rotation) to form dedicated, variable-bandwidth RF channels between specific ingress antennas and the egress antenna. "Demand for network capacity" is sensed by RF power meters and buffer occupancy at the ingress interfaces, feeding into the controller for real-time channel shaping and allocation. This enables L1-transparent RF transport without packet processing overhead within the metamaterial medium.

graph TD
    I1[Ingress RF Antenna 1] -- RF Data --> RFB(Metamaterial RF Bus)
    IN[Ingress RF Antenna N] -- RF Data --> RFB
    RFB -- Shaped RF Channel --> E[Egress RF Antenna]
    EI[Egress Controller] -- Demand for Capacity --> EI
    I1 -- Demand --> EI
    IN -- Demand --> EI
    EI -- Metamaterial Configuration Signals --> RFB

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Derivative 3.2: Operational Parameter Expansion - Planetary-Scale Inter-Constellation Satellite Link

Enabling Description:
This process applies dynamic L1 capacity allocation to a planetary-scale inter-constellation satellite communication link. The "network system" spans multiple Low Earth Orbit (LEO) satellite constellations (e.g., Starlink, OneWeb). "Ingress interfaces" are gateway earth stations or inter-satellite links (ISLs) from one constellation, while the "egress interface" is an ISL or gateway to another constellation or a deep-space probe. The "capacity pool" is the total available optical or RF spectrum across the inter-constellation links. "Demand for network capacity" is highly dynamic, driven by transient events (e.g., scientific data downlink from a planetary mission, surge in data traffic over a specific geographic region, unexpected celestial phenomena). The "optimizing" and "assigning" steps are performed by a distributed ground-segment control system (acting as the "egress interface" for allocation logic). This system dynamically allocates specific frequency bands, optical wavelengths, or time slots on high-power ISLs to specific "ingress interfaces" (e.g., a particular LEO satellite) based on real-time and predictive demand, maximizing throughput for time-critical or high-volume data transfers across vast distances, with L1 transparency across the satellite links.

sequenceDiagram
    participant GS1 as Gateway Earth Station 1 (Ingress)
    participant LEO1 as LEO Constellation 1 (Ingress ISL)
    participant LEO2 as LEO Constellation 2 (Egress ISL)
    participant GS2 as Gateway Earth Station 2 (Egress)
    participant DCS as Distributed Control System (Egress Logic)

    loop Repeating Process Cycle
        GS1->>DCS: Demand for Capacity (High-Res Image Data)
        LEO1->>DCS: Demand for Capacity (Telemetry Burst)
        DCS->>DCS: Optimizing Allocation (Planetary Scale)
        DCS->>LEO1: Assign Capacity Units (Wavelengths on ISL)
        DCS->>LEO2: Configure Egress (Receive Wavelengths)
        LEO1->>LEO2: Transport Data Packets (ISL @ L1)
        LEO2->>GS2: Transport Data Packets (Downlink @ L1)
    end

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Derivative 3.3: Cross-Domain Application - Bio-Nanobot Intracellular Data Transport

Enabling Description (Bio-Nanobot):
This process applies to a hypothetical data transport network within a biological system, specifically for inter-nanobot communication or data relay inside a cell. The "network system" consists of therapeutic bio-nanobots communicating within a cellular environment. "Ingress interfaces" are individual nanobots gathering biochemical data (e.g., protein concentrations, genetic markers). The "egress interface" is a command-and-control nanobot or a localized collection point for data fusion. The "capacity pool" is the available capacity of molecular communication channels (e.g., diffusion rates of signaling molecules, acoustic waves, or directed molecular motors). "Demand for network capacity" is driven by critical biological events detected by individual nanobots (e.g., detection of cancerous cells, viral replication, or drug delivery status). The "optimizing" and "assigning" steps are executed by the command-and-control nanobot, which dynamically modulates the emission rates of specific signaling molecules or activates specific molecular transport pathways to create variable-bandwidth "channels" from individual data-gathering nanobots. This ensures prioritized, L1-transparent transport of critical diagnostic data within the complex cellular environment.

graph TD
    N1[Nanobot 1 (Sensor)] -- Biochemical Data --> MCC(Molecular Comm Channel)
    NN[Nanobot N (Sensor)] -- Biochemical Data --> MCC
    MCC -- Data Flow --> CCON(Command & Control Nanobot)
    N1 -- Demand Signal --> CCON
    NN -- Demand Signal --> CCON
    CCON -- Allocate & Assign (Molecule Emission Rate) --> MCC

---

Derivative 3.4: Cross-Domain Application - Space-Based Manufacturing Data Synch

Enabling Description (Space-Based Manufacturing):
In an orbital manufacturing facility (e.g., 3D printing in microgravity), the "network system" manages data synchronization between distributed robotic fabricators, material handling systems, and a central manufacturing controller. "Ingress interfaces" are individual robotic fabrication units or material storage modules, generating telemetry, process parameters, and quality control data. The "egress interface" is the central manufacturing controller. The "capacity pool" is the total internal wireless (e.g., mmWave, laser) or wired communication bandwidth within the orbital facility. "Demand for network capacity" is dynamic, driven by real-time events such as critical component fabrication steps, sensor data bursts from defect detection, or material resupply operations. The "optimizing" and "assigning" steps are performed by the central manufacturing controller. It dynamically allocates dedicated, L1 communication channels (e.g., by adjusting antenna beamforming, frequency hopping patterns, or TDM/WDM assignments) to specific robotic units requiring high-bandwidth, low-latency data synchronization for precise coordinated movements or critical process adjustments, ensuring manufacturing integrity and efficiency.

graph TD
    R1[Robotic Fabricator 1] -- Telemetry/QC Data --> IN(Internal Network Bus)
    MHS[Material Handling System] -- Data --> IN
    IN -- Data Channels --> CMC[Central Manufacturing Controller]
    R1 -- Demand for Sync --> CMC
    MHS -- Demand for Sync --> CMC
    CMC -- Allocate & Assign (RF/Optical Slicing) --> IN

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Derivative 3.5: Integration with Emerging Tech - Quantum-Resistant Encrypted L1 with Decentralized Control

Enabling Description:
This process enhances the capacity allocation with quantum-resistant encryption at L1 and a decentralized control plane managed by a Distributed Ledger Technology (DLT).

• Quantum-Resistant Encryption (QRE) at L1: Each "source node specific connection" is secured with quantum-resistant encryption ciphers (e.g., lattice-based cryptography, hash-based signatures). This encryption is implemented directly at the L1 layer, prior to virtual concatenation, ensuring that even if the L1 channel is tapped, the data remains secure against future quantum attacks. The QRE key management is dynamically updated during the "process cycle."
• Decentralized Control with DLT: Instead of a single "egress interface" holding all "digital logic," the control plane logic for "optimizing" and "assigning" capacity is distributed across multiple trusted nodes, forming a consortium blockchain. "Demand for network capacity" from "ingress interfaces" is broadcast to this DLT network. Participating nodes collaboratively execute a smart contract (representing the allocation algorithm) to determine the capacity assignments. Once a consensus is reached, the validated "capacity allocation info" is recorded on the DLT and then pushed to the physical L1 network elements. This decentralization improves resilience, auditability, and trust in multi-operator or multi-tenant networks by eliminating a single point of control.

sequenceDiagram
    participant I1 as Ingress Interface 1
    participant IN as Ingress Interface N
    participant L1_NE as L1 Network Element
    participant DLT as Decentralized Ledger (Control Plane)

    loop Repeating Process Cycle
        I1->>L1_NE: Data (QRE Encrypted)
        IN->>L1_NE: Data (QRE Encrypted)
        I1->>DLT: Demand for Capacity (Signed Transaction)
        IN->>DLT: Demand for Capacity (Signed Transaction)
        DLT->>DLT: Smart Contract Executes Allocation Algorithm (Consensus)
        DLT->>L1_NE: Push Verified Allocation (QRE Key Update, L1 Config)
        L1_NE->>L1_NE: Assign L1 Channels
        L1_NE->>E: Transport Data
    end

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Derivative 3.6: The "Inverse" or Failure Mode - Diagnostic-First, Latency-Sacrificing Allocation

Enabling Description:
This "inverse" process prioritizes the capture and transport of diagnostic and debugging data over regular user traffic during system anomalies, even if it significantly increases latency for non-diagnostic traffic. During "normal" operation, the "optimizing" step aims for throughput. However, upon detection of system anomalies (e.g., high error rates, unexpected drops in throughput, hardware alerts, or specific network events), the "egress interface" (or an embedded anomaly detection module) immediately triggers a "diagnostic mode." In this mode, the "allocation of said capacity pool" is skewed to dedicate large L1 channels to internal diagnostic probes, logging interfaces, and fault isolation tools at the expense of regular data traffic. "Units of capacity" are preferentially assigned to data streams containing verbose debug logs, packet captures, or internal state dumps from "ingress interfaces" exhibiting anomalous behavior. The "transporting data packets" step becomes a high-priority conduit for troubleshooting data, allowing rapid fault isolation and resolution, even if it temporarily renders the network unusable for its primary purpose. This is a controlled, temporary degradation for the purpose of rapid repair.

stateDiagram
    [*] --> Normal_Operation
    Normal_Operation --> Anomaly_Detected: Error_Rate_Exceeds_Threshold | System_Alert
    Anomaly_Detected --> Diagnostic_Mode_Active: Prioritize_Diagnostic_Traffic
    Diagnostic_Mode_Active --> Regular_Traffic_Degraded: Skew_Allocation
    Diagnostic_Mode_Active --> Fault_Resolved: Anomaly_Cleared
    Fault_Resolved --> Normal_Operation
    Diagnostic_Mode_Active --> Permanent_Failure: Unresolved_Anomaly
    Permanent_Failure --> [*]

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Combination Prior Art Scenarios with Open-Source Standards

These scenarios combine the concepts of US Patent 7333511 with existing open-source standards to create obvious or non-novel prior art.

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Combination Prior Art 1: Dynamic L1 Bus with OpenFlow/SDN Control Plane

Enabling Description:
A network system incorporating the dynamically L1-channelizable packet transport bus as described in US7333511 (e.g., using SDH/SONET virtual concatenation for source-specific connections) is controlled by an OpenFlow-enabled SDN control plane. The "destination node" and "source nodes" of the bus are intelligent network elements (e.g., transponders, ROADMs, or virtual concatenation-capable switches) that expose their L1 channelization capabilities and capacity demand metrics (e.g., buffer occupancy) to a centralized SDN controller via a northbound API. The SDN controller, utilizing OpenFlow protocols (or similar SDN-specific protocols like NETCONF), acts as the "digital logic" that performs the "optimizing" and "assigning" steps. It collects "capacity demand figures" from the source nodes via OpenFlow agent statistics (e.g., OFPMP_PORT_STATS_REQUEST for buffer load) or custom extensions. Based on these demands and configured policies, the controller calculates the optimal L1 channel allocation (e.g., new STS-Xv or VC-3-Xv concatenation coefficients) and programs the underlying L1 network elements (the nodes) through OpenFlow flow modifications or equivalent NETCONF/YANG configurations. This reconfigures the L1 channels to adapt to real-time traffic loads, maximizing throughput while ensuring packet-layer transparency for data transport between source and destination nodes. The openflow-spec defines the communication between the controller and switches, providing the framework for dynamically adjusting network resources.

sequenceDiagram
    participant SC as SDN Controller
    participant SN as Source Node (OpenFlow Switch)
    participant DN as Destination Node (OpenFlow Switch)
    participant L1X as L1 Cross-Connect (managed by SN/DN)

    SC->>SN: Monitor Port Stats (e.g., buffer occupancy)
    SN->>SC: Report Traffic Load / Demand (OpenFlow Port Stats)
    SC->>SC: Optimizes L1 Channel Allocation based on Policies
    SC->>SN: Program L1 Channel (e.g., OpenFlow Flow Mod for VC-Xv)
    SC->>DN: Program L1 Channel (e.g., OpenFlow Flow Mod for VC-Xv)
    SN->>L1X: Configure VC-Xv for Source Channel
    L1X->>DN: Establish Dynamic L1 Channel
    SN->>L1X: Transport Data Packets (L1 Transparent)
    L1X->>DN: Transport Data Packets (L1 Transparent)

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Combination Prior Art 2: Dynamic L1 Bus with DPDK for High-Performance Node-Local Packet Handling

Enabling Description:
This combines the L1 channelization of US7333511 with the Data Plane Development Kit (DPDK) to enable ultra-high-performance packet handling at the "source nodes" and "destination node." Each source node and the destination node utilize DPDK-accelerated network interface cards (NICs) and user-space packet processing frameworks. When the "digital logic at the destination node" allocates "units of capacity" (e.g., STS-Xv or VC-3-Xv channels) on the L1 bus, these dynamically provisioned L1 channels are presented as virtual interfaces to the DPDK application running on the source and destination nodes. DPDK's rte_eth_dev_configure() and related APIs are used to program the NICs to transmit and receive packets directly onto/from these dynamically adjusted L1 virtual concatenated channels with zero-copy packet processing, bypassing the kernel network stack. This allows the nodes to efficiently generate "capacity demand figures" by monitoring DPDK ring buffer occupancy and to transport "data packets" over the dynamically allocated L1 channels at line rate with minimal CPU overhead, thus maximizing the end-to-end throughput. The DPDK framework ensures that the packet handling before and after the L1-transparent bus is extremely efficient and low-latency.

graph TD
    S[Source Node (DPDK Application)] -- Transmit Packet --> NIC_S[DPDK NIC (Source)]
    NIC_S -- Encapsulate (POS/Ethernet over VC-Xv) --> L1C_S[L1 Channel Input]
    L1C_S --> Bus[Dynamically L1 Channelized Bus]
    Bus --> L1C_D[L1 Channel Output]
    L1C_D -- Decapsulate --> NIC_D[DPDK NIC (Destination)]
    NIC_D -- Receive Packet --> D[Destination Node (DPDK Application)]

    S -- Buffer Occupancy (Demand) --> DL(Digital Logic at Destination)
    DL -- Allocate/Assign (VC-Xv Coeffs) --> Bus

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Combination Prior Art 3: Dynamic L1 Bus for Open RAN Fronthaul/Midhaul Optimization

Enabling Description:
This derivative integrates the dynamic L1 channelization principles of US7333511 into the Open Radio Access Network (Open RAN) architecture for optimizing fronthaul (between RU and DU) and midhaul (between DU and CU) transport. The "network system" spans the transport network interconnecting Open RAN components. The "ingress interfaces" are O-RAN Radio Units (RUs) sending digitized radio signals (e.g., eCPRI packets) or O-RAN Distributed Units (DUs) sending processed baseband data. The "egress interface" is an O-RAN Distributed Unit (DU) or Centralized Unit (CU) respectively. The "capacity pool" is the aggregate transport bandwidth (e.g., optical fiber, dedicated Ethernet) available for fronthaul/midhaul. "Demand for network capacity" is highly dynamic, driven by real-time radio traffic (e.g., user call activity, data downloads, massive MIMO requirements), 5G slicing demands, or specific radio resource allocation decisions. An O-RAN Service Management and Orchestration (SMO) framework, interacting with the O-RAN Non-Real-Time RIC (RAN Intelligent Controller) and Near-Real-Time RIC, acts as the "digital logic" that performs the "optimizing" and "assigning" steps. It dynamically allocates "units of capacity" (e.g., SDH/SONET VC-Xv paths, or dedicated Ethernet VLANs/segments as L1 channels) between RUs, DUs, and CUs. This allows for flexible and efficient allocation of L1 transport resources for latency-sensitive and bandwidth-intensive Open RAN traffic, adapting to changes in wireless network load and optimizing overall RAN performance without deep packet inspection within the L1 transport. The O-RAN A1 interface and O-RAN O1 interface would carry the demand and allocation signals.

sequenceDiagram
    participant RU as O-RAN Radio Unit (Ingress)
    participant DU as O-RAN Distributed Unit (Egress for Fronthaul, Ingress for Midhaul)
    participant CU as O-RAN Centralized Unit (Egress for Midhaul)
    participant SMO as O-RAN SMO (Non-RT RIC)
    participant NRT_RIC as O-RAN Near-RT RIC

    loop Repeating Process Cycle
        RU->>DU: eCPRI Data (L1 Transport)
        DU->>CU: Baseband Data (L1 Transport)
        RU->>NRT_RIC: Demand (via O1, e.g., cell load, latency)
        DU->>NRT_RIC: Demand (via O1, e.g., processing load, buffer)
        NRT_RIC->>SMO: Aggregate Demand (A1 Interface)
        SMO->>SMO: Optimizes L1 Transport Allocation for Fronthaul/Midhaul
        SMO->>NRT_RIC: Assign L1 Capacity (A1 Interface)
        NRT_RIC->>RU: Configure L1 Channel (e.g., eCPRI mapping)
        NRT_RIC->>DU: Configure L1 Channel (e.g., eCPRI mapping, midhaul slice)
        NRT_RIC->>CU: Configure L1 Channel (e.g., midhaul slice)
        RU->>DU: Transport Data over Optimized L1 Fronthaul
        DU->>CU: Transport Data over Optimized L1 Midhaul
    end