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Self-Compressive Approach for Distributed System Monitoring

by Akshada T Bhondave, Santoshkumar Biradar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 100 - Number 8
Year of Publication: 2014
Authors: Akshada T Bhondave, Santoshkumar Biradar
10.5120/17542-8126

Akshada T Bhondave, Santoshkumar Biradar . Self-Compressive Approach for Distributed System Monitoring. International Journal of Computer Applications. 100, 8 ( August 2014), 1-5. DOI=10.5120/17542-8126

@article{ 10.5120/17542-8126,
author = { Akshada T Bhondave, Santoshkumar Biradar },
title = { Self-Compressive Approach for Distributed System Monitoring },
journal = { International Journal of Computer Applications },
issue_date = { August 2014 },
volume = { 100 },
number = { 8 },
month = { August },
year = { 2014 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume100/number8/17542-8126/ },
doi = { 10.5120/17542-8126 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:29:23.847164+05:30
%A Akshada T Bhondave
%A Santoshkumar Biradar
%T Self-Compressive Approach for Distributed System Monitoring
%J International Journal of Computer Applications
%@ 0975-8887
%V 100
%N 8
%P 1-5
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Large-Scale distributed hosting infrastructures have become the basic platforms for several real-world production systems. But a challenging task is to achieve both scalability and high precision while monitoring a large number of intra-node attributes that contain information relating to each node and inter-node attribute that denote measurements between different nodes. This paper presents a new distributed monitoring framework Based on video coding techniques of named RBOIC (Replica Based Online Information Compression for Scalable Hosting Infrastructure Monitoring) which uses novel image based approach in which system models snapshots of the monitored distributed system images and applies lightweight online reference block search algorithm to compress monitoring traffic from worker to management node to achieve scalable full coverage monitoring. RBOIC explores the design, implementation of adaptive rood pattern search algorithm to find out optimal or near optimal reference values for each attribute. RBOIC effectively achieve failure-resilient monitoring by restoring monitoring data on replica node. The experimental evaluation of compressive monitoring system has been done using real time monitoring data . The experimental results show that RBOIC can achieve much higher compression ratios with less overhead and adaptive rood pattern search (APRS) achieves better performance by preventing unnecessary intermediate search than diamond search pattern.

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Index Terms

Computer Science
Information Sciences

Keywords

Distributed System Monitoring Online Data Compression Adaptive Rood Search Pattern

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