SDN Controller Failure Handling via Probing and Quorum Logic
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Solution Overview
Problem
Complex network configurations and troubleshooting in software-defined networks (SDNs) are error-prone and challenging due to the complexity of configuration processes and the difficulty in identifying root causes of failures, leading to inconsistent network behavior.
Innovation Solution
A system and method for handling failure scenarios during data collection and assurance in SDNs by probing controllers for status information, determining a quorum, collecting logical models, and performing assurance analysis operations to identify and address inconsistencies and errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If network operators use a wide array of configuration options to tailor the network, then network flexibility and control are improved, but network complexity increases
Solution Approach 1:
The patent segments the network configuration management into modular components including policy templates, configuration profiles, and hierarchical policy structures. This allows complex network configurations to be broken down into manageable, reusable units that maintain flexibility while reducing overall system complexity through organized modularity.
Solution Approach 2:
The patent employs parameter-driven configuration where network behavior is controlled through configurable parameters and variables. By changing parameters rather than restructuring entire configurations, operators can maintain flexibility and adaptability while working within a standardized framework that prevents complexity escalation.
2Measurement precision
If comprehensive data collection is performed during network assurance, then measurement precision is improved, but time consumption increases
Solution Approach 1:
The patent implements preliminary data collection and analysis operations before failure scenarios occur. By proactively gathering baseline network state information, configuration data, and performance metrics in advance, the system reduces the time required for accurate failure detection while maintaining comprehensive measurement precision when failures do occur.
Solution Approach 2:
The patent employs selective data collection strategies that skip unnecessary verification steps when confidence levels are high. During normal operation, the system collects essential data at optimized intervals rather than continuously, rushing through routine checks while maintaining precision for critical failure detection through targeted deep analysis when anomalies are detected.
3Reliability
If detailed assurance analysis operations are performed, then reliability is improved, but device complexity increases
Solution Approach 1:
The patent introduces intermediary components including policy templates, configuration profiles, and abstraction layers between the raw network data and the assurance analysis operations. These intermediaries standardize and simplify the data representation, allowing detailed and reliable analysis to be performed without directly increasing the complexity of the core analysis system.
Solution Approach 2:
The patent creates simplified copies and representations of complex network states through logical models and abstracted data structures. By working with these copied representations rather than raw network data, the system can perform detailed assurance analysis with high reliability while keeping the analysis system itself relatively simple through standardized model-based approaches.
Data Source
AI summary
Systems, methods, and computer-readable media for handling failure scenarios during data collection and analysis for assurance. In some examples, a system can obtain a logical model of a network and, based on the logical model, identify a plurality of controllers on the network and a plurality of nodes on a fabric of the network. The system can probe the plurality of controllers and plurality of nodes for respective status information, including respective reachability information, respective login diagnostics information, and/or respective software information. Based on the respective status information, the system can determine conditions at the plurality of controllers and the plurality of nodes and define one or more assurance operations based on the conditions at the plurality of controllers and the plurality of nodes. The system can then perform the one or more assurance operations.