University of Bahrain
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A Novel Workload Allocation Strategy for Batch Jobs

Show simple item record Shenfield,A. Fleming, P. J. 2018-07-31T08:39:36Z 2018-07-31T08:39:36Z 2013
dc.identifier.issn 2210-1519
dc.description.abstract The distribution of computational tasks across a diverse set of geographically distributed heterogeneous resources is a critical issue in the realisation of true computational grids. Conventionally, workload allocation algorithms are divided into static and dynamic approaches. Whilst dynamic approaches frequently outperform static schemes, they usually require the collection and processing of detailed system information at frequent intervals - a task that can be both time consuming and unreliable in the real-world. This paper introduces a novel workload allocation algorithm for optimally distributing the workload produced by the arrival of batches of jobs. Results show that, for the arrival of batches of jobs, this workload allocation algorithm outperforms other commonly used algorithms in the static case. A hybrid scheduling approach (using this workload allocation algorithm), where information about the speed of computational resources is inferred from previously completed jobs, is then introduced and the efficiency of this approach demonstrated using a real world computational grid. These results are compared to the same workload allocation algorithm used in the static case and it can be seen that this hybrid approach comprehensively outperforms the static approach. en_US
dc.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri *
dc.subject Workload Allocation
dc.subject Adaptive Resources Scheduling
dc.subject Grid Computing
dc.title A Novel Workload Allocation Strategy for Batch Jobs en_US
dc.type Article en_US
dc.volume 01
dc.issue 01
dc.source.title International Journal of Computing and Network Technology
dc.abbreviatedsourcetitle IJCNT

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