Memory Consumption Monitoring via Garbage Collection Correlation
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Solution Overview
Problem
Monitoring memory consumption in high-traffic application servers is challenging as it can significantly impact system performance, and existing methods do not effectively correlate node content service requests with garbage collection events to identify suspicious memory usage.
Innovation Solution
Implementing a correlation analysis between garbage collection events and service requests to identify suspicious activities that lead to excessive memory use, using a statistical evaluation to calculate a correlation value that indicates memory consumption patterns, allowing for targeted monitoring and reporting of such requests with minimal system impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If memory consumption monitoring is implemented in high-traffic application servers, then system stability is improved, but system performance deteriorates
Solution Approach 1:
The patent applies partial monitoring by focusing only on specific garbage collection events and associated service requests rather than continuously monitoring all memory operations. The system selectively triggers monitoring based on GC event occurrence, performing detailed analysis only when necessary (during GC events) rather than continuously, thus reducing overall performance impact while maintaining system stability.
2Measurement precision
If continuous memory monitoring is performed, then memory consumption is detected, but system performance significantly deteriorates
Solution Approach 1:
The patent implements periodic monitoring triggered by garbage collection events rather than continuous monitoring. The system monitors memory consumption at specific intervals when GC events occur, collecting data about service requests during these periodic moments. This periodic approach provides sufficient measurement precision for detecting memory issues while avoiding the performance penalty of continuous monitoring.
3Measurement precision
If detailed monitoring of all service requests is implemented, then suspicious memory usage is identified, but monitoring overhead increases
Solution Approach 1:
The patent extracts and focuses monitoring efforts on specific subsets of service requests - namely those associated with garbage collection events. Rather than monitoring all service requests equally, the system extracts and analyzes only the requests that occurred during GC events, storing them in data structures for later analysis. This extraction approach enables precise identification of suspicious memory usage patterns while minimizing monitoring overhead by ignoring unrelated requests.
Data Source
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AI summary
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