Adaptive Cluster Timer Manager for Cascading Timeout Errors
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Solution Overview
Problem
In multi-node systems, loosely managed timers can lead to cascading timeout errors, causing nodes to be deemed out of service and potentially bringing down the entire system due to inappropriate timeout settings that are not aligned with inter-relationships between tasks and timers.
Innovation Solution
A hierarchical approach to timer management is introduced, where timers are structured based on their inter-relationships, with a cluster-wide mechanism initiating adjustments and node-based mechanisms performing actual adjustments, ensuring that timers are set according to dependencies and system conditions, and their timeout periods are dynamically adjusted based on monitored performance and configuration data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If timers are set individually and loosely based on developer understanding, then timer configuration is simple and flexible, but timeout errors occur frequently and cascade across multiple tasks
Solution Approach 1:
The system dynamically changes timer timeout parameters based on monitored system conditions and task inter-relationships. Instead of using fixed timeout values, the timer manager adjusts timeout periods according to actual system state, preventing both premature timeouts and excessive waiting periods.
Solution Approach 2:
The timer manager implements feedback mechanisms by monitoring task completion status, system load, and timeout patterns. This feedback is used to adaptively adjust timer settings, allowing the system to learn from past timeout events and improve timeout management over time.
2Adaptability or versatility
If multiple timers are managed independently without coordination, then each task can have its own timeout settings, but near-simultaneous timeout errors occur causing nodes to be deemed out of service
Solution Approach 1:
The patent merges individual timer management into a unified cluster-wide timer manager that coordinates timeout settings across all nodes. This centralized coordination prevents synchronized timeout events while maintaining task-specific flexibility through the hierarchical timer structure.
Solution Approach 2:
The timer management system is segmented into hierarchical levels: cluster-wide timer settings for coordination, node-level timers for local management, and task-specific timers for individual timeout control. This segmentation allows each level to operate independently within its scope while maintaining overall system coherence.
3Reliability
If timer timeout values are set to accommodate slow tasks, then fewer timeout errors occur, but task completion time increases and system productivity decreases
Solution Approach 1:
The timer system transitions from static timeout values to dynamic timeout adjustment. Timeout periods are continuously adapted based on real-time system conditions, task progress monitoring, and historical performance data, allowing the system to optimize between reliability and productivity.
Solution Approach 2:
The timer manager autonomously adjusts timeout values without external intervention by monitoring task execution patterns and system state. This self-service capability allows the system to automatically optimize timeout settings for both reliability and productivity based on observed performance.
Data Source
AI summary
Described herein are techniques for adaptively managing timers that are used in various layers of a node. In many cases, the number of timers that occur in the system is reduced by proactively and reactively adjusting values of the timers based on conditions affecting the system, thereby making such a system to perform significantly better and more resiliently than otherwise.