Network Redundancy Configuration via Service Level Evaluation
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Solution Overview
Problem
Current data center networks face challenges in evaluating and optimizing the service levels of network devices and applications due to the complexity of redundancy configurations and the lack of comprehensive methods to compare devices based on their failure characteristics and service levels, leading to potential availability and reliability issues.
Innovation Solution
A method and system for characterizing service levels of network devices and applications by analyzing performance data, evaluating redundant configurations, and configuring network traffic to meet specified service level constraints, utilizing data center event logs and statistical models to assess device reliability and availability, and identifying optimal configurations for redundancy groups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant network devices are deployed to improve availability, then network reliability is improved, but device complexity increases
Solution Approach 1:
The patent segments the network into distinct redundancy groups where each group contains multiple network devices that can independently fail without affecting overall network availability. This segmentation allows complex redundancy configurations to be managed through modular groups, reducing the complexity of analyzing and configuring the entire network system.
Solution Approach 2:
The patent implements a feedback mechanism where service level data is continuously collected from network devices and used to dynamically adjust redundancy configurations. This feedback loop enables the system to automatically optimize availability based on real-time performance data, reducing the need for manual complexity management.
2Ease of manufacture
If network devices are compared based on functionality alone, then procurement cost is reduced, but service level assessment accuracy deteriorates
Solution Approach 1:
The patent changes the parameters used for device comparison from functional specifications to service level metrics. By collecting and analyzing actual service level data (availability, failure characteristics) rather than relying on manufacturer specifications, the system enables accurate cost-service level analysis that reflects real-world performance.
Solution Approach 2:
The patent replaces traditional mechanical comparison methods (specification sheets, functional comparisons) with a data-driven statistical analysis system. This substitution allows for more precise service level assessment by using actual performance data and statistical models rather than theoretical specifications.
3Measurement precision
If comprehensive service level evaluation methods are implemented, then service level assessment accuracy is improved, but system complexity increases
Solution Approach 1:
The patent creates a universal evaluation framework that can assess service levels across different network device types and redundancy configurations using the same methodology. This multi-functional approach simplifies the evaluation system by providing a single comprehensive method that works for various network scenarios without requiring device-specific complex analysis tools.
Solution Approach 2:
The patent uses statistical models that replicate actual network behavior patterns to predict service levels. By copying and analyzing historical failure data and performance patterns through statistical distributions, the system can accurately assess future service levels without requiring complex real-time simulation systems.
Data Source
AI summary
The described implementations relate to computer networking. One implementation is a method performed using one or more computing devices. The method can include obtaining first performance data reflecting performance by first networking components of a first classification and, based at least on the first performance data, determining a first expected service level of a first redundant configuration of the first networking components. The method can also include obtaining second performance data reflecting performance by second networking components of a second classification, and, based at least on the second performance data, determining a second expected service level of a second redundant configuration of the second networking components. The method can also include providing an evaluation of the first redundant configuration and the second redundant configuration based at least on first expected service level and the second expected service level, and configuring network traffic based at least on the evaluation.