Title
Gossip-Based Distributed Algorithms For Estimating The Average Load Of Scalable Clusters And Grids
Abstract
We present gossip-based distributed algorithms by which each node of a cluster or a grid can find an estimate of the global average load of the system. Knowledge of this estimate can improve the performance by allowing each node to make better scheduling decisions. Our algorithms are based on asynchronous exchanges (gossip) of load messages between either a random or a fixed pairs of nodes. We show that based on these messages, each node can find an estimate of the average load of all the nodes. We present the algorithms and prove their convergence.
Year
Venue
Keywords
2004
PDPTA '04: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON PARALLEL AND DISTRIBUTED PROCESSING TECHNIQUES AND APPLICATIONS, VOLS 1-3
cluster computing, distributed computing, gossip-based algorithms, grid computing
Field
DocType
Citations 
Cluster (physics),Computer science,Parallel computing,Gossip,Distributed algorithm,Distributed computing,Scalability
Conference
2
PageRank 
References 
Authors
0.40
1
2
Name
Order
Citations
PageRank
Amnon Barak1590119.00
Zvi Drezner21195140.69