Resilient Routing for Session Initiation Protocol Systems
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Solution Overview
Problem
Existing communication systems face challenges in managing primary/backup and failover/failback relationships in networked environments, particularly in determining when to assign users to primary or backup clusters and ensuring seamless communication between them, due to complexities in health check processes and consensus reaching in multi-master systems.
Innovation Solution
A distributed handover mechanism is implemented to manage primary/backup relationships, using a sequence-based algorithm for server health monitoring and configurable thresholds for failover and failback intervals, allowing for automated detection of cluster health and flexible configuration of backup clusters, and maintaining a cache for optimized routing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If primary/backup relationships are used to assign users to clusters, then fault tolerance is improved, but device complexity increases due to health check processes and consensus reaching in multi-master systems
Solution Approach 1:
The patent introduces a distributed handover mechanism that acts as an intermediary between primary and backup clusters. This mechanism includes a handover coordinator that manages failover decisions and a handover executor that implements the actual failover, thereby simplifying the complex health check and consensus reaching processes in multi-master systems while maintaining fault tolerance
Solution Approach 2:
The failover management system is segmented into distinct functional components: health check modules that monitor cluster status, handover coordinator that makes failover decisions, and handover executor that implements failover actions. This segmentation reduces overall system complexity by dividing the monolithic health check and consensus process into manageable, independent modules
2Productivity
If automated failover mechanisms are implemented, then productivity is improved through seamless failover, but device complexity increases due to distributed handover mechanisms and global knowledge requirements
Solution Approach 1:
The distributed handover mechanism enables clusters to autonomously determine their own health status through local health checks and automatically execute failover decisions based on pre-configured policies. This self-service capability eliminates the need for centralized control, improving productivity through seamless automated failover while managing complexity through decentralized decision-making
Solution Approach 2:
The system pre-configures failover policies, health check parameters, and handover sequences before failures occur. The handover coordinator maintains a cache of cluster status information and pre-determines failover candidates, enabling rapid automated failover execution without complex real-time negotiations, thus improving productivity while controlling complexity
3Measurement precision
If health check processes are performed to determine cluster status, then measurement precision is improved, but loss of time occurs due to consensus reaching delays in multi-master systems
Solution Approach 1:
The health check process operates periodically with predetermined intervals and sequences. The handover coordinator schedules regular health status checks of primary and backup clusters, and when failures are detected, follows a predetermined sequence for failover execution. This periodic approach ensures accurate cluster status determination while minimizing time loss by avoiding ad-hoc consensus negotiations
Solution Approach 2:
The distributed handover mechanism implements feedback loops where health check results are continuously monitored and fed back to the handover coordinator. When health status changes are detected, the system automatically triggers appropriate failover actions based on pre-configured policies, eliminating delays associated with manual consensus reaching while maintaining precise cluster health determination
Data Source
AI summary
Resilient routing management approaches are provided based on primary/backup and failover/failback relationships in a clustered network environment, where each user and/or resource is assigned to a primary cluster and at least one backup cluster. A distributed handover mechanism enables global knowledge of primary/backup relationships between clusters and their assigned users or resources.