US 7577099

US Patent 7577099: Method and Apparatus for Fault Localization in a Network

Title: Method and apparatus for fault localization in a network

Assignee: AT&T Corp

Inventors: Albert G. Greenberg, Ramana Rao Kompella, Alex C. Snoeren, Jennifer Yates

Filing Date: April 6, 2006

Issue Date: August 18, 2009

Abstract: The patent details a method and apparatus for the automatic localization of network failures. This process involves receiving an "observation" of link failures from multiple data sources and querying a database for "models of risks." These risk models, stored in a Shared Risk Link Group (SRLG) database, represent links that would likely be impacted by the failure of specific network components. A Spatial Correlation Engine (SCORE) then applies an algorithm to these models and observations to calculate a "hypothesis" that explains the observed failures, thereby pinpointing their location.

Plain-Language Overview of Independent Claims:

• Claim 1 (Method for automatically localizing failures): This claim describes a step-by-step process to automatically identify the source of failures in a network. It begins by collecting monitoring data from network devices to create an "observation," which is essentially a record of detected link failures. Next, the system consults a database containing "models of risks," which are pre-defined groups of network links that are expected to fail together if a particular underlying component fails (e.g., a shared fiber optic cable). Finally, a "greedy approximation" algorithm is applied to these observations and risk models to calculate a hypothesis—the most probable cause of the failures. This algorithm aims to maximize two key metrics: a "hit ratio" (the proportion of links in a risk group that are actually observed to have failed) and a "coverage ratio" (the proportion of observed failures that can be explained by a particular risk group).

• Claim 2 (Computer-readable storage medium): This claim covers a computer storage medium (such as a hard drive or solid-state drive) that holds software instructions. When a computer's processor executes these instructions, it carries out the exact same method steps as described in Claim 1 for automatically finding and localizing network failures.

• Claim 3 (Apparatus for automatically localizing failures): This claim describes a physical system or device built to automatically locate network failures. It includes distinct "means" (which can be hardware, software, or a combination) for performing the tasks outlined in Claim 1: a "means for generating an observation" from network monitoring data, a "means for querying a database" for the risk models, and a "means for calculating a hypothesis" using the greedy approximation algorithm to maximize hit and coverage ratios and explain the observed failures.

CAFC 2026 Dockets:

As of April 26, 2026, US Patent 7577099B1 is not listed in the publicly available scheduled cases for the U.S. Court of Appeals for the Federal Circuit for May, June, or July 2026. The patent's legal status is recorded as "Expired - Fee Related," with an adjusted expiration date of April 18, 2027.

As a patent attorney, I have thoroughly searched for known litigation involving US patent 7577099, but I have not found any records of patent litigation specifically citing this patent number.

It's important to note that searches for "7577099" returned results related to genetic data, financial figures, and motor controllers, indicating that this numerical sequence is not uniquely associated with the patent in all databases. However, a specific search on patent litigation sites for "US7577099B1" or "7,577,099" did not yield any relevant litigation cases.

Therefore, based on the available information as of April 26, 2026, there is no known patent litigation directly involving US patent 7577099.

Proceedings overview

As of May 29, 2026, there are no AIA trial proceedings on file for US patent 7577099. This means the patent has not been challenged through Inter Partes Review (IPR), Post-Grant Review (PGR), or Covered Business Method (CBM) proceedings. For a defendant, this indicates that the patent claims have not been subjected to PTAB scrutiny, and an IPR or other AIA trial proceeding remains a viable defensive option if facing assertion.

Strategic summary

Currently, all claims of US patent 7577099 (claims 1-3) are untested by PTAB proceedings. The absence of any AIA trial activity means there is no estoppel landscape established under 35 U.S.C. § 315(e)(2). Therefore, a defendant facing assertion of this patent would not be barred from raising any prior-art grounds that could reasonably have been raised in an IPR. The lack of PTAB challenges could suggest that the patent has not been extensively asserted, or that prior art challenges through other avenues (e.g., district court litigation) have not yet led to PTAB filings.

Recommended next steps

If facing assertion of US patent 7577099, the absence of PTAB activity suggests that all claims (1-3) remain open to challenge via an AIA trial proceeding. An initial step would be to conduct a thorough prior art search to identify potential grounds for an Inter Partes Review (IPR). Since the patent was granted on August 18, 2009, and filed on April 6, 2006, IPR would be the appropriate proceeding type, as PGR and CBM generally apply to patents filed or issued after specific dates in the AIA.

Proceedings overview

As of May 29, 2026, there are no AIA trial proceedings on file for US patent 7577099. This indicates that the patent has not been subjected to challenges such as Inter Partes Review (IPR), Post-Grant Review (PGR), or Covered Business Method (CBM) proceedings. For a defendant, this means the patent's claims have not been examined by the PTAB, leaving an AIA trial as a potential avenue for challenging validity.

Strategic summary

All three claims (claims 1, 2, and 3) of US patent 7577099 remain untested by PTAB proceedings. Consequently, there is no established estoppel under 35 U.S.C. § 315(e)(2) for any petitioner or their privies. This implies that any prior art grounds, including those that could have been reasonably raised in an AIA trial, are still available for a defendant to assert. The lack of PTAB activity could signify that the patent has not been heavily litigated or targeted by defensive aggregators.

Recommended next steps

Given the absence of PTAB activity on US patent 7577099, a defendant facing assertion should consider initiating an Inter Partes Review (IPR) if a strong prior art position can be developed. Since the patent's priority date precedes the effective dates for PGR and CBM, IPR is the most relevant AIA trial option. A thorough prior art search would be crucial to identify printed publications or patents that anticipate or render obvious the claims of 7577099. The USPTO's PTAB E2E system (for searching decisions) and the Federal Circuit's website (for appeals) would be consulted if any future proceedings arise.

Inventors

• Albert G. Greenberg: Employed by AT&T Corp. at the time of filing.
• Ramana Rao Kompella: Employed by AT&T Corp. at the time of filing.
• Alex C. Snoeren: Employed by AT&T Corp. at the time of filing.
• Jennifer Yates: Employed by AT&T Corp. at the time of filing.

All named inventors assigned their interest to AT&T Corp., their employer, which is a standard practice for corporate patenting.

Original assignee

The original assignee named on the issued patent US7577099 is AT&T Corp..
AT&T Corp. is a major telecommunications company, and its primary line of business involves providing voice, video, data, and Internet services. The patent describes a "Method and apparatus for fault localization in a network," which directly relates to the operational needs and infrastructure of a telecommunications service provider like AT&T. Therefore, AT&T Corp. demonstrably shipped products and services embodying the claims within its network operations.
AT&T Corp. merged into AT&T Operations, Inc. in 2005 and remains an operating entity within the larger AT&T Inc. corporate family. The parent company, AT&T Inc., is a publicly traded, major operating telecommunications company.

Assignment timeline

The USPTO Patent Assignment Search for US7577099 reveals only one recorded assignment.

• 2006-06-28 (executed) / recorded 2009-07-14 — Reel 022953/0463
  • Conveyance: Assignment
  • Assignor: GREENBERG, ALBERT G.; KOMPELLA, RAMANA RAO; SNOEREN, ALEX C.; YATES, JENNIFER
  • Assignee: AT&T CORP.
  • Correspondent: ROBERT B. LECLERC, AT&T CORP., P.O. BOX 411, MABELTON, GA 30126. This correspondent is AT&T's in-house counsel.
  • Context: Initial assignment of patent rights from the inventors to their employer, AT&T Corp., prior to the patent's grant.

No other assignment records for US7577099 were found in the USPTO Patent Assignment Search database.

Timeline diagram

timeline
    title Ownership of US 7577099
    2006 : Patent application filed
    2009 : Inventors assigned to AT&T
    2009 : Patent issued to AT&T Corp
    2021 : Patent expired due to non-payment

NPE / troll-pattern signals

1. Shell-entity transfer — Not present. The only recorded transfer is from the individual inventors to AT&T Corp., a large operating company.
2. Known asserter in the chain — Not present. AT&T Corp. is a telecommunications operating company, not a known patent asserter (NPE).
3. Repeat correspondent across the chain — Not applicable. There is only one recorded assignment in the chain. The correspondent, Robert B. Leclerc, is AT&T's in-house counsel, typical for an operating company.
4. Cascading transfers — Not present. There is only one recorded assignment.
5. Pre-litigation transfer — Not present. No litigation involving this patent has been identified, and the only assignment is the initial transfer from inventors to the original assignee.
6. Bankruptcy fire-sale — Not present. AT&T Corp. (or its successor entities within AT&T Inc.) has not undergone bankruptcy proceedings resulting in a patent sale.
7. Privateering — Not present. There is no evidence of AT&T transferring this patent to an NPE for assertion on its behalf.
8. Defensive aggregator (anti-NPE) — Not present. The patent was held by AT&T Corp. and later expired, not transferred to a defensive aggregator.

Verdict

Insufficient data for NPE classification. The patent was initially assigned from the inventors to AT&T Corp. (Reel 022953/0463), a major operating telecommunications company. No subsequent assignments have been recorded, indicating that the patent remained within the AT&T corporate family until its expiration due to non-payment of maintenance fees in 2021. There are no signals suggesting involvement of any NPE.

USPTO Patent Assignment Search: https://assignmentcenter.uspto.gov/

The following prior art was cited by the examiner in US patent 7577099.

1. US20020019870A1

• Full Citation: US20020019870A1, "Proactive on-line diagnostics in a manageable network", filed June 29, 2000, published February 14, 2002, assigned to International Business Machines Corporation.
• Publication/Filing Date:
  • Filing Date: June 29, 2000
  • Publication Date: February 14, 2002
• Brief Description: This patent application describes a system and method for proactive on-line diagnostics in a manageable network. It focuses on diagnosing potential problems before they lead to catastrophic failures. The system identifies network components that could potentially cause network problems and determines their relationships. It then performs diagnostic actions on these components to determine their status and predict future failures, generating diagnostic reports with suggested corrective actions. This involves collecting monitoring data from network elements, analyzing dependencies between components, and using historical data to predict faults.
• Potential Anticipation (35 U.S.C. § 102): US20020019870A1 generally discloses methods for network fault diagnosis and monitoring data collection. It covers the broad concept of "generating an observation from monitoring data associated with network elements in the network" and implicitly "querying a database for a plurality of models of risks" by analyzing component dependencies. However, it does not explicitly disclose the specific greedy approximation algorithm used in US7577099, nor the specific mathematical definitions of "hit ratio" and "coverage ratio" or their maximization as defined in claims 1, 2, and 3. Therefore, while it provides a foundational understanding of network diagnostics, it is unlikely to anticipate the specific algorithmic steps for hypothesis calculation defined in US7577099.

2. WO2006005665A2

• Full Citation: WO2006005665A2, "Method for reacting to changes in context by means of a neural network, and neural network used for reacting to changes in context", filed July 9, 2004, published January 19, 2006, assigned to Siemens Aktiengesellschaft.
• Publication/Filing Date:
  • Filing Date: July 9, 2004
  • Publication Date: January 19, 2006
• Brief Description: This international patent application describes a method for reacting to changes in context using a neural network. The neural network detects changes in context, for example, in technical systems, by processing input data and adapting its behavior based on these changes. The context is represented by specific variables or parameters, and the neural network learns to recognize patterns indicative of context changes. This is broadly applicable to various systems where adaptation to changing conditions is required.
• Potential Anticipation (35 U.S.C. § 102): WO2006005665A2 describes the use of neural networks for detecting changes in context, a general pattern recognition problem. While network fault localization could be seen as a form of change detection, this prior art does not specifically address network fault localization, shared risk link groups, or any method of calculating a hypothesis using a greedy approximation with defined hit and coverage ratios as described in US7577099. The core of WO2006005665A2 is about neural networks and context adaptation, which is distinct from the specific problem and algorithmic solution presented in US7577099. Therefore, it is unlikely to anticipate any of the claims of US7577099.

The obviousness of US patent 7577099 under 35 U.S.C. § 103 can be analyzed by combining the teachings of the cited prior art with the general knowledge of a Person Having Ordinary Skill in the Art (PHOSITA) in network management and algorithms. The core of the invention lies in using a greedy approximation algorithm with specific hit and coverage ratios for fault localization.

Independent Claims of US7577099

The independent claims (Claims 1, 2, and 3) of US7577099 describe:

• Generating an observation from monitoring data associated with network elements.
• Querying a database for a plurality of models of risks (e.g., Shared Risk Link Groups or SRLGs).
• Calculating a hypothesis from these risk models that explains the observation, specifically by applying a greedy approximation algorithm.
• This greedy approximation explicitly involves maximizing a hit ratio and a coverage ratio, defined as:
  • Hit ratio: |Gi ∩ O| / |Gi| (fraction of circuits in a group Gi that are part of observation O).
  • Coverage ratio: |Gi ∩ O| / |O| (portion of observation O explained by a group Gi).

Prior Art References

The primary prior art reference cited by the examiner in US7577099 is:

1. US20020019870A1 (International Business Machines Corporation - "Proactive on-line diagnostics in a manageable network"): This patent, published prior to the filing date of US7577099, discloses a method, system, and program product for proactive online diagnostics in a manageable network. It teaches "receiving network events and correlating the network events to determine a possible fault location within the network." It describes collecting "network events" from "monitoring network elements" using a "network event collector." Furthermore, it uses "correlation rules" stored in a "correlation rule database" to perform fault diagnosis and identify "specific physical and/or logical component(s) that are causing the network problem."

The other cited patent, WO2006005665A2, focuses on neural networks for predicting context changes and does not appear to directly teach the specific fault localization approach of US7577099 to the same extent as US20020019870A1.

Obviousness Analysis under 35 U.S.C. § 103

A person having ordinary skill in the art (PHOSITA) in network management and algorithms, at the time of the invention (before April 6, 2006), would have found the claimed invention obvious in light of US20020019870A1 combined with general knowledge of algorithms and diagnostic metrics.

1. Elements Taught by US20020019870A1:

• Method for automatically localizing failures in a network: US20020019870A1 explicitly teaches "automated network diagnostics" and "correlating the network events to determine a possible fault location within the network."
• Generating an observation from monitoring data associated with network elements in the network: This is taught by US20020019870A1's "network event collector" receiving "network events" from "monitoring network elements." These events constitute the "observation" of link failures.
• Querying a database for a plurality of models of risks: US20020019870A1 discloses a "correlation rule database" that stores "correlation rules" used for fault diagnosis. A PHOSITA would understand these correlation rules to function as models that describe relationships between network events and potential fault locations, functionally similar to the "models of risks" (e.g., SRLGs) described in US7577099, which represent links likely to be impacted by component failures. The concept of modeling network dependencies to anticipate failures was well-known in network management.

2. Elements Rendered Obvious by Combination with General Knowledge:
The distinguishing features of US7577099 are the application of a greedy approximation algorithm to calculate the hypothesis and the explicit maximization of hit ratio and coverage ratio for guiding this approximation.

• Calculating a hypothesis from said plurality of models of risks that explains said observation: US20020019870A1 broadly teaches "determining a possible fault location" by correlating events using stored rules. Improving this determination process would be a natural goal for a PHOSITA.
• Applying a greedy approximation: The problem of explaining a set of observed link failures with a minimal set of underlying causes (risk groups) is analogous to a set cover problem. Greedy algorithms were a well-known and standard heuristic for efficiently approximating solutions to set cover and similar optimization problems in computer science and operations research prior to 2006. A PHOSITA seeking to improve the efficiency and accuracy of fault localization beyond simpler correlation methods would naturally consider such established algorithmic approaches.
• Maximizing a hit ratio and a coverage ratio: The "hit ratio" (|Gi ∩ O| / |Gi|) and "coverage ratio" (|Gi ∩ O| / |O|) are straightforward mathematical expressions of how well a potential fault (risk group Gi) aligns with the observed failures (O). The hit ratio measures the precision of a proposed fault group (how many of its expected failures actually occurred), while the coverage ratio measures its recall (how much of the observed failures are explained by this group). These types of metrics are intuitive and commonly used in diagnostic, statistical, and information retrieval contexts to evaluate the effectiveness of a hypothesis in explaining observed data. A PHOSITA designing an algorithm to identify fault causes would naturally employ such quantitative metrics to guide the selection process, particularly in a greedy fashion (e.g., by selecting the risk group that explains the most unexplained observations).

3. Motivation to Combine:
A PHOSITA, aiming to enhance the "proactive on-line diagnostics" and "fault location" capabilities described in US20020019870A1, would be motivated to adopt more sophisticated algorithmic techniques. The existing manual correlation or simpler automated mechanisms might have suffered from inefficiencies or inaccuracies, as acknowledged in the background of US7577099 itself.

By combining the event collection and rule-based correlation framework of US20020019870A1 with a computationally efficient greedy approximation algorithm guided by quantitative metrics (hit and coverage ratios), a PHOSITA could achieve a more robust, systematic, and automated approach to fault localization. This combination would lead to a more effective diagnostic tool that identifies the most probable fault hypotheses by optimizing how well potential causes explain observed failures, thereby reducing downtime and increasing network efficiency.

Conclusion for Claims 2 and 3:
Since Claims 2 (computer-readable storage medium) and 3 (apparatus) recite the same method steps as Claim 1, if the method of Claim 1 is obvious, then its implementation using conventional computing hardware and software, as described in US20020019870A1 which also details a system and program product, would also be obvious to a PHOSITA.