GEMS: Gossip-Enabled Monitoring Service for Scalable Heterogeneous Distributed Systems

GEMS: Gossip-Enabled Monitoring Service for Scalable Heterogeneous Distributed Systems

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by Rajagopal Subramaniyan , Pirabhu Raman , Alan D. George , Matthew Radlinski

Venue:	Cluster Comput
Citations:	2 - 0 self

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Datum	Value	Source
TITLE	GEMS: Gossip-Enabled Monitoring Service for Scalable Heterogeneous Distributed Systems	SVM HeaderParse 0.2
AUTHOR NAME	Rajagopal Subramaniyan	SVM HeaderParse 0.2
AUTHOR AFFIL	High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida,; P.O. Box 116200, Gainesville	SVM HeaderParse 0.2
AUTHOR ADDR	FL 32611-6200	SVM HeaderParse 0.2
AUTHOR NAME	Pirabhu Raman	SVM HeaderParse 0.2
AUTHOR AFFIL	High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida,; P.O. Box 116200, Gainesville	SVM HeaderParse 0.2
AUTHOR ADDR	FL 32611-6200	SVM HeaderParse 0.2
AUTHOR NAME	Alan D. George	SVM HeaderParse 0.2
AUTHOR AFFIL	High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida,; P.O. Box 116200, Gainesville	SVM HeaderParse 0.2
AUTHOR ADDR	FL 32611-6200	SVM HeaderParse 0.2
AUTHOR NAME	Matthew Radlinski	SVM HeaderParse 0.2
AUTHOR AFFIL	High-performance Computing and Simulation (HCS) Research Laboratory, Department of Electrical and Computer Engineering, University of Florida,; P.O. Box 116200, Gainesville	SVM HeaderParse 0.2
AUTHOR ADDR	FL 32611-6200	SVM HeaderParse 0.2
ABSTRACT	Abstract. Gossip protocols have proven to be effective means by which failures can be detected in large, distributed systems in an asynchronous manner without the limitations associated with reliable multicasting for group communications. In this paper, we discuss the development and features of a Gossip-Enabled Monitoring Service (GEMS), a highly responsive and scalable resource monitoring service, to monitor health and performance information in heterogeneous distributed systems. GEMS has many novel and essential features such as detection of network partitions and dynamic insertion of new nodes into the service. Easily extensible, GEMS also incorporates facilities for distributing arbitrary system and application-specific data. We present experiments and analytical projections demonstrating scalability, fast response times and low resource utilization requirements, making GEMS a potent solution for resource monitoring in distributed computing.	SVM HeaderParse 0.2
VENUE	Cluster Comput	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	2006	INFERENCE
CITATIONS	19 found	ParsCit 1.0