Patent 12452192

Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Derivative works

Defensive disclosure: derivative variations of each claim designed to render future incremental improvements obvious or non-novel.

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Defensive Disclosure for Innovations Derived from US Patent 12,452,192

Publication Date: April 26, 2026
Subject: Derivative Methods and Systems for Optimized Network Connection Management
Field: Computer Networking, Telecommunications, Distributed Systems

This document discloses a series of derivative inventions, applications, and technical variations related to the core concepts described in US Patent 12,452,192 ("Systems and methods for providing a global virtual network (GVN)"). The purpose of this disclosure is to place these concepts into the public domain, thereby establishing them as prior art for any future patent applications.

The core concept involves a control server monitoring a plurality of access point servers, generating a performance-based ranked list of said access points, and providing this list to an endpoint device to facilitate an automated, optimized connection via a secure tunnel. The following disclosures expand upon this foundation.

Axis 1: Material & Component Substitution

1.1 Quantum-Secured Tunneling via QKD

  • Enabling Description: The secure tunnel between the endpoint device and the access point server is established using cryptographic keys exchanged via a Quantum Key Distribution (QKD) network. The control server's performance monitoring subsystem is extended to include metrics from the QKD management layer, such as Quantum Bit Error Rate (QBER) and secure key generation rate. The access point ranking algorithm is modified to weigh both classical network performance (latency, bandwidth) and quantum channel stability. An endpoint device receives a list of access points ranked by their suitability for establishing a quantum-secured connection, and uses the distributed quantum key to initialize a symmetric encryption protocol (e.g., AES-256) for the data tunnel.

  • Diagram:

    sequenceDiagram
    participant EPD as Endpoint Device
    participant CS as Control Server
    participant QKDN as QKD Network
    participant AP as Access Point Server

    EPD->>CS: Request Ranked AP List
    CS->>QKDN: Query QBER & Key Rate for APs
    QKDN-->>CS: Return Quantum Channel Metrics
    CS->>CS: Generate Hybrid Rank (Network + Quantum)
    CS-->>EPD: Provide Ranked AP List
    EPD->>QKDN: Establish Secure Key with Top AP
    QKDN-->>EPD: Distribute Symmetric Key
    EPD->>AP: Initiate Tunnel using Quantum Key
    AP-->>EPD: Tunnel Established

1.2 Neuromorphic Endpoint for Real-Time Correlation

  • Enabling Description: The endpoint device incorporates a neuromorphic processing unit (NPU) for connection selection. The control server provides a standard performance-ranked list. Concurrently, the NPU on the endpoint processes high-dimensional, real-time local data streams (e.g., RF spectrum analysis, accelerometer data indicating motion, local CPU load). The NPU executes a spiking neural network (SNN) model trained to find correlations between the ranked list and the local context. For example, it may learn that a specific access point, though ranked highest by the control server, performs poorly when the device is in motion. The NPU overrides the primary ranking to select a more contextually appropriate access point, enabling faster and more robust decision-making than a traditional CPU could perform.

  • Diagram:

    flowchart TD
    A[Control Server] -->|Ranked List| B(Endpoint CPU)
    C[Local Sensors <br/> e.g., RF, GPS] -->|Real-time Data Stream| D(Endpoint NPU)
    B --> E{Decision Logic}
    D -->|Contextual Override Signal| E
    E -->|Final AP Selection| F[Network Interface]
    F --> G((Top-Ranked Access Point))

1.3 FPGA-Based Reconfigurable Access Points

  • Enabling Description: The access point servers are implemented on Field-Programmable Gate Array (FPGA) platforms rather than general-purpose CPUs. The control server's role is expanded to that of an FPGA configuration manager. It maintains a library of hardware "gateware" configurations, each optimized for a specific task (e.g., low-latency video transcoding, bulk data compression, specific firewall ruleset acceleration). The performance ranking sent to endpoints includes not only network metrics but also the currently loaded gateware profile on each AP. An endpoint requiring low-latency video streaming would select the AP that is currently configured with the video transcoding gateware, even if its raw network latency is marginally higher than another AP.

  • Diagram:

    classDiagram
    ControlServer : +List<GatewareProfile>
    ControlServer : +getRankedAPList(service_type)
    ControlServer : +pushGateware(AP_ID, Profile_ID)
    EndpointDevice : -service_requirement
    EndpointDevice : +selectAP(ranked_list)
    AccessPoint_FPGA : -current_gateware_profile
    AccessPoint_FPGA : +processTraffic()
    ControlServer "1" -- "N" AccessPoint_FPGA : Manages
    EndpointDevice "1" -- "1" AccessPoint_FPGA : Connects to

Axis 2: Operational Parameter Expansion

2.1 Deep-Space Delay-Tolerant Network (DTN) GVN

  • Enabling Description: The system is applied to interplanetary communications. Endpoints are planetary rovers or deep-space probes. Access points are relay satellites in various orbits. The control server is a ground-based mission control. Performance metrics are dominated by multi-minute latencies and predictable transmission windows based on orbital mechanics. The ranking algorithm uses an ephemeris database to predict future link availability and quality. Tunnels are established using a delay-tolerant protocol like the Bundle Protocol (RFC 5050), where data is transmitted in store-and-forward "bundles." The ranked list informs the endpoint which relay satellite currently offers the highest probability of a successful bundle forward towards Earth.

  • Diagram:

    graph TD
    subgraph Mars
        A[Rover - Endpoint]
    end
    subgraph Space
        B[Mars Orbiter 1 - AP]
        C[Deep Space Relay 1 - AP]
        D[Earth Orbiter 1 - AP]
    end
    subgraph Earth
        E[Ground Station - Control Server]
    end

    A -- Bundle Protocol Tunnel --> B
    B -- Store & Forward --> C
    C -- Store & Forward --> D
    D -- Downlink --> E
    E -- Ephemeris-Based Ranked List --> C
    C -- Forwarded List --> B
    B -- Forwarded List --> A

2.2 High-Frequency Trading (HFT) GVN

  • Enabling Description: The system operates to minimize latency in the nanosecond range for High-Frequency Trading. Endpoints are trading algorithms, and access points are gateways within different exchange colocation facilities (e.g., NY4, LD4). The control server monitors network performance using specialized hardware timestamping (PTP, Precision Time Protocol) and collects market data feeds to gauge exchange matching engine load. The ranked list is updated thousands of times per second. The "tunnel" is a kernel-bypass connection (e.g., using RDMA or DPDK) established directly from the trading application to the chosen exchange gateway. The ranking prioritizes the lowest combination of network latency and perceived order queue time at the exchange.

  • Diagram:

    sequenceDiagram
    participant TA as Trading Algorithm (EPD)
    participant CS as HFT Control Server
    participant EXG1 as Exchange Gateway 1 (AP)
    participant EXG2 as Exchange Gateway 2 (AP)

    loop High-Frequency Update Loop
        CS->>EXG1: Probe Latency & Queue Depth
        CS->>EXG2: Probe Latency & Queue Depth
        CS->>CS: Generate Nanosecond-Ranked List
        CS-->>TA: Stream Ranked List Update
    end
    TA->>TA: Select top AP from latest update
    TA-xEXG1: Establish Kernel-Bypass Tunnel
    TA->>EXG1: Send Market Order

Axis 3: Cross-Domain Application

3.1 Agricultural Drone Swarm C2

  • Enabling Description: The system manages command and control (C2) for a swarm of agricultural drones (endpoints) surveying a large area. Access points consist of fixed 5G base stations and mobile ground vehicles with high-gain antennas. The control server, running on the farm's central management system, ranks access points based on signal strength, interference, and the backhaul capacity relative to the drone's mission (e.g., a drone streaming 4K video requires higher capacity). Each drone dynamically and independently switches its C2 tunnel to the highest-ranked access point, ensuring uninterrupted control and data backhaul even as it moves across vast and varied terrain.

  • Diagram:

    flowchart LR
    subgraph Drone Swarm (Endpoints)
        D1(Drone 1)
        D2(Drone 2)
        D3(Drone N)
    end
    subgraph C2 Access Points
        AP1[5G Tower]
        AP2[Mobile Command Truck]
        AP3[Aerostat Balloon]
    end
    CS(Farm Control Server)

    D1 -- C2 Tunnel --> AP2
    D2 -- C2 Tunnel --> AP1
    D3 -- C2 Tunnel --> AP1

    CS -- Performance Monitoring --> AP1
    CS -- Performance Monitoring --> AP2
    CS -- Performance Monitoring --> AP3
    CS -- Ranked List --> D1
    CS -- Ranked List --> D2
    CS -- Ranked List --> D3

3.2 Distributed Power Grid Load Balancing

  • Enabling Description: This system is applied to a smart power grid. Endpoints are substation controllers and large-scale battery storage facilities. Access points are regional data concentrators. The control server is the central grid operations center. The system is used to route critical SCADA control traffic. Access points are ranked based on communication channel latency, reliability, and cybersecurity posture (e.g., number of detected intrusion attempts). A substation controller (endpoint) will automatically route its control data through the most reliable and secure access point to ensure commands for load shedding or grid balancing are delivered with minimal delay and maximal integrity.

  • Diagram:

    erDiagram
    GRID_OPERATIONS_CENTER {
        string ControlServer_ID
    }
    DATA_CONCENTRATOR {
        string AP_ID
        float Latency
        float Reliability
        int SecurityScore
    }
    SUBSTATION {
        string Endpoint_ID
    }
    GRID_OPERATIONS_CENTER ||--o{ DATA_CONCENTRATOR : "monitors"
    GRID_OPERATIONS_CENTER }o--|| SUBSTATION : "sends ranked list to"
    SUBSTATION ||--|{ DATA_CONCENTRATOR : "tunnels through"

Axis 4: Integration with Emerging Tech

4.1 AI-Driven Predictive Path Selection

  • Enabling Description: The control server integrates a machine learning model (e.g., an LSTM network) to provide predictive rankings. The model is trained on historical performance data, BGP routing announcements, time-of-day traffic patterns, and even public network outage information. Instead of ranking APs on their current state, it predicts their likely state 5 minutes into the future. The ranked list sent to the endpoint is a forecast, allowing the endpoint to proactively establish a tunnel with an AP that is predicted to be optimal, avoiding connections that are currently good but likely to degrade soon.

  • Diagram:

    stateDiagram-v2
    state "Collect Historical Data" as Collect
    state "Train LSTM Model" as Train
    state "Real-time Monitoring" as Monitor
    state "Predict Future State" as Predict
    state "Generate Ranked List" as Rank
    state "Distribute to Endpoint" as Distribute

    [*] --> Collect
    Collect --> Train
    Train --> Predict
    Monitor --> Predict : Feeds Current State
    Predict --> Rank
    Rank --> Distribute
    Distribute --> [*]

4.2 Blockchain-Verified Performance & Billing

  • Enabling Description: A permissioned blockchain is used to create an immutable record of AP performance and usage. The control server acts as an oracle, committing signed performance metrics (latency, uptime, packet loss) for each AP to the blockchain at regular intervals. When an endpoint establishes a tunnel, a smart contract is initiated. This contract logs the data transferred through the AP. At the end of the session, the contract automatically calculates billing based on the logged data volume and the quality of service recorded on-chain, providing a transparent and auditable "proof of performance" for service level agreements.

  • Diagram:

    sequenceDiagram
    participant EPD
    participant CS as Control Server
    participant AP
    participant BC as Blockchain

    CS->>BC: commitPerformanceMetrics(AP, Metrics)
    EPD->>CS: Request AP List
    CS-->>EPD: Return Ranked List with Pointers to BC
    EPD->>BC: verifyHistoricalPerformance(AP)
    EPD->>AP: Initiate Tunnel (triggers Smart Contract)
    BC->>BC: Smart Contract Deployed
    Note over EPD, AP: Data Transfer Session
    AP->>BC: logDataVolume(EPD, Volume)
    EPD->>AP: End Tunnel
    BC->>BC: Finalize Smart Contract (billing, settlement)

Axis 5: The "Inverse" or Failure Mode

5.1 Graceful Degradation for Energy-Constrained IoT

  • Enabling Description: For battery-powered IoT endpoints, the system supports a low-power mode. When battery level drops below a threshold, the endpoint sends a request_low_power_list to the control server. The control server's ranking algorithm switches from a latency/throughput model to an energy-per-bit model, prioritizing APs reachable with the lowest transmission power. The endpoint establishes a "thin tunnel" using a lightweight protocol like CoAP or MQTT-SN and reduces its data transmission frequency. This ensures critical connectivity is maintained for the longest possible duration.

  • Diagram:

    flowchart TD
    A[EPD: Battery < 20%] --> B{Send Request};
    B -- request_low_power_list --> C[Control Server];
    C -- Run Energy-per-Bit Algorithm --> D[Generate Low-Power Ranked List];
    D --> E[EPD Receives List];
    E --> F[Select Most Power-Efficient AP];
    F --> G[Establish Thin Tunnel (CoAP/DTLS)];
    G --> H(Transmit Low-Frequency Telemetry);

5.2 Decentralized Failsafe via Peer Beacons

  • Enabling Description: To handle control server failure, all devices support a decentralized failsafe mode. If an endpoint cannot reach the control server after a set number of retries, it enters "discovery mode." All access point servers are configured to periodically broadcast signed UDP beacon packets containing their identity and self-reported health metrics (e.g., CPU load, active connection count). The endpoint listens for these beacons, validates their signatures, and builds a temporary, local ranked list. It then connects to the best available AP based on this decentralized information, ensuring service continuity until the central controller is restored.

  • Diagram:

    stateDiagram-v2
    state "Centralized Mode" as Cent
    state "Discovery Mode" as Disc
    state "Failsafe Connection" as Fail

    [*] --> Cent
    Cent --> Disc : Control Server Unreachable
    Disc --> Disc : Listen for AP Beacons
    Disc --> Fail : Local Best AP Found
    Fail --> Cent : Control Server Reachable
    Cent --> [*]

Combination Prior Art Scenarios

  1. Combination with WireGuard Protocol: The secure tunnel mechanism is implemented using the open-source WireGuard protocol. The control server distributes a ranked list of AP IP addresses, each accompanied by the corresponding WireGuard public key and allowed IP subnets. The endpoint device, using a standard WireGuard client, simply ingests the configuration for the top-ranked peer and establishes the connection, benefiting from WireGuard's high performance and modern cryptography.

  2. Combination with Prometheus Monitoring: The entire performance monitoring infrastructure is built on open-source components. Each access point runs a Prometheus Node Exporter and a custom exporter for network metrics (e.g., blackbox_exporter for latency probes). The control server runs a central Prometheus server that scrapes this data. The ranking logic is implemented as a set of complex PromQL queries, and the final ranked list is generated by a service that queries the Prometheus API.

  3. Combination with QUIC Transport Protocol: The system leverages the open-source QUIC protocol for both control plane communication and data plane tunnels. Endpoints establish QUIC connections to the control server. The ranked list provided by the server allows the endpoint to use QUIC's Connection Migration feature. If the performance of the primary AP degrades, the endpoint can migrate its active QUIC connection to the next-best AP on the list seamlessly, without tearing down and re-establishing the transport session, providing near-instantaneous failover.

Generated 5/10/2026, 12:34:24 AM