Memory Leak Detection in Distributed System

Due to memory leaks, often-valuable system memory gets wasted and denied for other processes thereby affecting the computational performance. If an application-s memory usage exceeds virtual memory size, it can leads to system crash. Current memory leak detection techniques for clusters are reactive and display the memory leak information after the execution of the process (they detect memory leak only after it occur). This paper presents a Dynamic Memory Monitoring Agent (DMMA) technique. DMMA framework is a dynamic memory leak detection, that detects the memory leak while application is in execution phase, when memory leak in any process in the cluster is identified by DMMA it gives information to the end users to enable them to take corrective actions and also DMMA submit the affected process to healthy node in the system. Thus provides reliable service to the user. DMMA maintains information about memory consumption of executing processes and based on this information and critical states, DMMA can improve reliability and efficaciousness of cluster computing.

Authors:

• Roohi Shabrin S.
• Devi Prasad B.
• Prabu D.
• Pallavi R. S.
• Revathi P.

Keywords:

• Dynamic Memory Monitoring Agent (DMMA)
• Cluster Computing
• Memory Leak
• Fault Tolerant Framework
• Dynamic Memory Leak Detection (DMLD).

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