Object Age Detection in Garbage Collection Heaps
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional profiling tools for Java-based systems are limited in detecting object ages in garbage collection heaps, leading to inefficiencies in memory leak detection and system performance issues, particularly in large-scale distributed environments where memory leaks can cause critical Out Of Memory Errors (OOME) and performance problems.
Innovation Solution
A system and method for determining object ages in garbage collection heaps by tracking the number of garbage collections each object has survived, grouping objects into age ranges, and communicating these ages between virtual machines, allowing for on-demand profiling without restarting the VM, thus enabling effective memory leak detection and performance monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional profiling tools are used to detect memory leaks, then memory leak detection capability is provided, but the tools require restarting the VM which disrupts user sessions and causes performance degradation
Solution Approach 1:
The system performs preliminary actions by integrating the profiling mechanism directly into the JVM during runtime, allowing memory leak detection to be prepared and executed without external tool intervention or VM restart, thus maintaining system availability
Solution Approach 2:
The patent introduces an intermediary profiling agent that operates within the JVM to bridge the gap between memory leak detection needs and system continuity, enabling detection without requiring external tools that would necessitate VM restart
2Reliability
If conventional profiling tools are used for memory analysis, then memory leak detection is enabled, but memory consumption increases and system resources are heavily utilized
Solution Approach 1:
The system applies partial action by selectively profiling only specific objects and memory regions that are suspected of memory leaks, rather than analyzing the entire heap, thus reducing overall memory consumption while maintaining effective detection capability
Solution Approach 2:
The patent changes parameters by dynamically adjusting profiling depth, object sampling rates, and analysis granularity based on system conditions, allowing the profiler to adapt its resource usage to available system capacity while maintaining detection effectiveness
3Measurement precision
If object ages are not tracked in garbage collection heaps, then profiling simplicity is maintained, but memory leak detection precision is insufficient
Solution Approach 1:
The system segments the heap into age-based generations and tracks objects independently in each segment, allowing precise memory leak detection through age analysis while managing complexity by organizing tracking data into structured, manageable segments rather than a monolithic system
Data Source
AI summary
A system and method are provided for object age detection in garbage collection heaps. In one embodiment, ages of objects in a garbage collection heap at a first virtual machine at a server are determined by detecting a number of garbage collections each object has survived. An age is associated to each object according to the determined ages. The objects are grouped in age ranges, wherein the age ranges correspond to the determined ages. The age ranges are communicated to a second virtual machine at a client.