Genetic algorithm in finding Pareto frontier of optimizing data transfer versus job execution in grids-Reference-Cited by-同舟云学术

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Genetic algorithm in finding Pareto frontier of optimizing data transfer versus job execution in grids

Published:2012-11-22 Issue:6 Volume:28 Page:1715-1736
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat.: Pract. Exper.

Author:

Taheri Javid¹,Zomaya Albert Y.¹,Khan Samee U.²

Affiliation:

1. School of Information Technologies; The University of Sydney; Sydney NSW 2006 Australia

2. Department of Electrical Engineering; North Dakota State University; Fargo USA

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference31 articles.

1. CERN 2011 Compact Muon Solenoid (CMS) http://public.web.cern.ch/public/en/lhc/CMS-en.html

2. Bulk scheduling with the DIANA scheduler;Anjum;IEEE Transactions on Nuclear Science,2006

3. Cooperative power-aware scheduling in grid computing environments;Subrata;Journal of Parallel and Distributed Computing,2010

4. Grid Computing

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data-Aware Task Allocation for Achieving Low Latency in Collaborative Edge Computing;IEEE Internet of Things Journal;2019-04

2. Workshop on high performance data intensive computing;Concurrency and Computation: Practice and Experience;2016-01-15

3. Hopfield neural network for simultaneous job scheduling and data replication in grids;Future Generation Computer Systems;2013-10

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