research-article

Using artificial life techniques for distributed grid job scheduling

Authors:

Simone A. LudwigAuthors Info & Claims

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

Pages 1091 - 1097

https://doi.org/10.1145/1529282.1529522

Published: 08 March 2009 Publication History

Abstract

Grids are an emerging infrastructure providing distributed access to computational and storage resources. Handling many incoming requests at the same time and distributing the workload efficiently is a challenge which load balancing algorithms address. Current load balancing implementations for the Grid are central in nature and therefore prone to the single point of failure problem. This paper introduces two distributed artificial life-inspired load balancing algorithms using Ant Colony Optimization and Particle Swarm Optimization. Distributed load balancing stands out as a robust algorithm in regard to any topology changes in the network. The implementation details are given and evaluation results show the efficiency of the two distributed load balancing algorithms.

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Cited By

Patel DTripathy DTripathy C(2016)Survey of load balancing techniques for GridJournal of Network and Computer Applications10.1016/j.jnca.2016.02.01265:C(103-119)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.02.012
Niemi TKommeri JHameri A(2013)Improving Energy-Efficiency of Scientific Computing ClustersIndustrial Engineering10.4018/978-1-4666-1945-6.ch103(1916-1933)Online publication date: 2013
https://doi.org/10.4018/978-1-4666-1945-6.ch103
Brocco A(2013)The grid, the load and the gradientNatural Computing: an international journal10.1007/s11047-012-9323-z12:1(69-85)Online publication date: 1-Mar-2013
https://dl.acm.org/doi/10.1007/s11047-012-9323-z
Show More Cited By

Index Terms

Using artificial life techniques for distributed grid job scheduling
1. Computing methodologies
  1. Artificial intelligence
    1. Control methods
    2. Search methodologies
2. Theory of computation
  1. Design and analysis of algorithms
    1. Algorithm design techniques
      1. Dynamic programming

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Published In

cover image ACM Conferences

SAC '09: Proceedings of the 2009 ACM symposium on Applied Computing

March 2009

2347 pages

ISBN:9781605581668

DOI:10.1145/1529282

Conference Chairs:
Sung Y. Shin
South Dakota State University, United States
,
Sascha Ossowski
University Rey Juan Carlos, Spain

Copyright © 2009 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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New York, NY, United States

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Published: 08 March 2009

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SAC09: The 2009 ACM Symposium on Applied Computing

March 8, 2009 - March 12, 2008

Hawaii, Honolulu

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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Cited By

Patel DTripathy DTripathy C(2016)Survey of load balancing techniques for GridJournal of Network and Computer Applications10.1016/j.jnca.2016.02.01265:C(103-119)Online publication date: 1-Apr-2016
https://dl.acm.org/doi/10.1016/j.jnca.2016.02.012
Niemi TKommeri JHameri A(2013)Improving Energy-Efficiency of Scientific Computing ClustersIndustrial Engineering10.4018/978-1-4666-1945-6.ch103(1916-1933)Online publication date: 2013
https://doi.org/10.4018/978-1-4666-1945-6.ch103
Brocco A(2013)The grid, the load and the gradientNatural Computing: an international journal10.1007/s11047-012-9323-z12:1(69-85)Online publication date: 1-Mar-2013
https://dl.acm.org/doi/10.1007/s11047-012-9323-z
Niemi TKommeri JHameri AKaabouch NHu W(2012)Improving Energy-Efficiency of Scientific Computing ClustersEnergy-Aware Systems and Networking for Sustainable Initiatives10.4018/978-1-4666-1842-8.ch001(1-19)Online publication date: 2012
https://doi.org/10.4018/978-1-4666-1842-8.ch001
Brocco AFolino GMastroianni CMostaghim SSuzuki J(2011)ozmosProceedings of the 3rd workshop on Biologically inspired algorithms for distributed systems10.1145/1998570.1998573(9-16)Online publication date: 14-Jun-2011
https://dl.acm.org/doi/10.1145/1998570.1998573
Niemi THameri A(2011)Memory-based scheduling of scientific computing clustersThe Journal of Supercomputing10.1007/s11227-011-0612-661:3(520-544)Online publication date: 22-Apr-2011
https://doi.org/10.1007/s11227-011-0612-6
Ludwig SMoallem A(2011)Swarm Intelligence Approaches for Grid Load BalancingJournal of Grid Computing10.1007/s10723-011-9180-59:3(279-301)Online publication date: 1-Sep-2011
https://dl.acm.org/doi/10.1007/s10723-011-9180-5
Nasir HKu-Mahamud KDin A(2010)Load Balancing Using Enhanced Ant Algorithm in Grid ComputingProceedings of the 2010 Second International Conference on Computational Intelligence, Modelling and Simulation10.1109/CIMSiM.2010.29(160-165)Online publication date: 28-Sep-2010
https://dl.acm.org/doi/10.1109/CIMSiM.2010.29
El Kabbany GWanas NHegazi NShaheen S(2010)A Dynamic Load Balancing Framework for Real-time Applications in Message Passing SystemsInternational Journal of Parallel Programming10.1007/s10766-010-0134-539:2(143-182)Online publication date: 25-May-2010
https://doi.org/10.1007/s10766-010-0134-5

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