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Job replication on multiserver systems

Part of: Computer system organization Operations research and management science

Published online by Cambridge University Press:  01 July 2016

Yusik Kim ,
Rhonda Righter  and
Ronald Wolff
Yusik Kim*
Affiliation:
University of California, Berkeley
Rhonda Righter*
Affiliation:
University of California, Berkeley
Ronald Wolff*
Affiliation:
University of California, Berkeley
*
∗ Postal address: Department of Industrial Engineering and Operations Research, 4141 Etcheverry Hall, Berkeley, CA 94720, USA.
∗ Postal address: Department of Industrial Engineering and Operations Research, 4141 Etcheverry Hall, Berkeley, CA 94720, USA.
∗ Postal address: Department of Industrial Engineering and Operations Research, 4141 Etcheverry Hall, Berkeley, CA 94720, USA.
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Abstract

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Parallel processing is a way to use resources efficiently by processing several jobs simultaneously on different servers. In a well-controlled environment where the status of the servers and the jobs are well known, everything is nearly deterministic and replicating jobs on different servers is obviously a waste of resources. However, in a poorly controlled environment where the servers are unreliable and/or their capacity is highly variable, it is desirable to design a system that is robust in the sense that it is not affected by the poorly performing servers. By replicating jobs and assigning them to several different servers simultaneously, we not only achieve robustness but we can also make the system more efficient under certain conditions so that the jobs are processed at a faster rate overall. In this paper we consider the option of replicating jobs and study how the performance of different ‘degrees’ of replication, ranging from no replication to full replication, affects the performance of a system of parallel servers.

Keywords

Stochastic schedulinggrid computingjob replication

MSC classification

Primary: 68M20: Performance evaluation; queueing; scheduling
Secondary: 90B36: Scheduling theory, stochastic 90B22: Queues and service

Information

Type
General Applied Probability
Information
Advances in Applied Probability , Volume 41 , Issue 2 , June 2009 , pp. 546 - 575
Copyright
Copyright © Applied Probability Trust 2009 

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