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Article: Parallel physics-inspired waterflow particle mechanics algorithm for load rebalancing

TitleParallel physics-inspired waterflow particle mechanics algorithm for load rebalancing
Authors
KeywordsApproximation Algorithm
Distributed And Parallel Algorithm
Load Rebalancing
Nature-Inspired Algorithm
Waterflow Particle Mechanics Model
Issue Date2010
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/comnet
Citation
Computer Networks, 2010, v. 54 n. 11, p. 1767-1777 How to Cite?
AbstractThe Load Rebalancing Problem (LRP) that reassigns tasks to processors so as to minimize the maximum load arises in the context of dynamic load balancing. Many applications such as on Web based environment, parallel computing on clusters can be stated as LRP. Solving LRP successfully would allow us to utilize resources better and achieve better performance. However LRP has been proven to be NP-hard, thus generating the exact solutions in tractable amount of time becomes infeasible when the problems become large. We present a new nature-inspired approximation algorithm based on the Waterflow Particle Mechanics (W-PM) model to compute in parallel approximate efficient solutions for LRPs. Just like other Nature-inspired Algorithms (NAs) drawing from observations of physical processes that occur in nature, the W-PM algorithm is inspired by kinematics and dynamics of waterflow. The W-PM algorithm maps the classical LRP to the flow of water flows in channels by corresponding mathematical model in which all water flows flow according to certain defined rules until reaching a stable state. By anti-mapping the stable state, the solution to LRP can be obtained. © 2010 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/152437
ISSN
2015 Impact Factor: 1.446
2015 SCImago Journal Rankings: 0.755
ISI Accession Number ID
Funding AgencyGrant Number
National Natural Science Foundation of China60905043
General Research Fund of Hong Kong Research Grant Council7137/08E
Chinese Universities Scientific Fund
Funding Information:

This work was supported by the National Natural Science Foundation of China under Grant No.60905043, the General Research Fund of Hong Kong Research Grant Council under Grant No.7137/08E and Chinese Universities Scientific Fund.

References

 

DC FieldValueLanguage
dc.contributor.authorFeng, Xen_US
dc.contributor.authorLau, FCMen_US
dc.date.accessioned2012-06-26T06:39:03Z-
dc.date.available2012-06-26T06:39:03Z-
dc.date.issued2010en_US
dc.identifier.citationComputer Networks, 2010, v. 54 n. 11, p. 1767-1777en_US
dc.identifier.issn1389-1286en_US
dc.identifier.urihttp://hdl.handle.net/10722/152437-
dc.description.abstractThe Load Rebalancing Problem (LRP) that reassigns tasks to processors so as to minimize the maximum load arises in the context of dynamic load balancing. Many applications such as on Web based environment, parallel computing on clusters can be stated as LRP. Solving LRP successfully would allow us to utilize resources better and achieve better performance. However LRP has been proven to be NP-hard, thus generating the exact solutions in tractable amount of time becomes infeasible when the problems become large. We present a new nature-inspired approximation algorithm based on the Waterflow Particle Mechanics (W-PM) model to compute in parallel approximate efficient solutions for LRPs. Just like other Nature-inspired Algorithms (NAs) drawing from observations of physical processes that occur in nature, the W-PM algorithm is inspired by kinematics and dynamics of waterflow. The W-PM algorithm maps the classical LRP to the flow of water flows in channels by corresponding mathematical model in which all water flows flow according to certain defined rules until reaching a stable state. By anti-mapping the stable state, the solution to LRP can be obtained. © 2010 Elsevier B.V. All rights reserved.en_US
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/comneten_US
dc.relation.ispartofComputer Networksen_US
dc.subjectApproximation Algorithmen_US
dc.subjectDistributed And Parallel Algorithmen_US
dc.subjectLoad Rebalancingen_US
dc.subjectNature-Inspired Algorithmen_US
dc.subjectWaterflow Particle Mechanics Modelen_US
dc.titleParallel physics-inspired waterflow particle mechanics algorithm for load rebalancingen_US
dc.typeArticleen_US
dc.identifier.emailLau, FCM:fcmlau@cs.hku.hken_US
dc.identifier.authorityLau, FCM=rp00221en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.comnet.2010.02.002en_US
dc.identifier.scopuseid_2-s2.0-77955423179en_US
dc.identifier.hkuros211448-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-77955423179&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume54en_US
dc.identifier.issue11en_US
dc.identifier.spage1767en_US
dc.identifier.epage1777en_US
dc.identifier.isiWOS:000280258300004-
dc.publisher.placeNetherlandsen_US
dc.identifier.scopusauthoridFeng, X=55200149100en_US
dc.identifier.scopusauthoridLau, FCM=7102749723en_US
dc.identifier.citeulike6753858-

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