File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1109/ICCS.2008.4737190
- Scopus: eid_2-s2.0-62949187444
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: A new nature-inspired algorithm for load balancing
Title | A new nature-inspired algorithm for load balancing |
---|---|
Authors | |
Keywords | Approximation Algorithm Distributed And Parallel Algorithm Load Balancing Nature-Inspired Algorithm Particle Mechanics Model |
Issue Date | 2008 |
Citation | 2008 11Th Ieee Singapore International Conference On Communication Systems, Iccs 2008, 2008, p. 289-293 How to Cite? |
Abstract | The classical Load Balancing Problem (LBP) is to map tasks to processors so as to minimize the maximum load. Solving the LBP successfully would lead to better utilization of resources and better performance. The LBP has been proven to be NP-hard, thus generating the exact solutions in a tractable amount of time becomes infeasible when the problems become large. We present a new nature-inspired approximation algorithm based on the Particle Mechanics (PM) model to compute in parallel approximate efficient solutions for LBPs. Just like other Nature-inspired Algorithms (NAs) drawing from observations of physical processes that occur in nature, the PM algorithm is inspired by physical models of particle kinematics and dynamics. The PM algorithm maps the classical LBP to the movement of particles in a force field by a corresponding mathematical model in which all particles move according to certain defined rules until reaching a stable state. By anti-mapping the stable state, the solution to LBP can be obtained. © 2008 IEEE. |
Persistent Identifier | http://hdl.handle.net/10722/151943 |
References |
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Feng, X | en_US |
dc.contributor.author | Lau, FCM | en_US |
dc.contributor.author | Shuai, D | en_US |
dc.date.accessioned | 2012-06-26T06:31:16Z | - |
dc.date.available | 2012-06-26T06:31:16Z | - |
dc.date.issued | 2008 | en_US |
dc.identifier.citation | 2008 11Th Ieee Singapore International Conference On Communication Systems, Iccs 2008, 2008, p. 289-293 | en_US |
dc.identifier.uri | http://hdl.handle.net/10722/151943 | - |
dc.description.abstract | The classical Load Balancing Problem (LBP) is to map tasks to processors so as to minimize the maximum load. Solving the LBP successfully would lead to better utilization of resources and better performance. The LBP has been proven to be NP-hard, thus generating the exact solutions in a tractable amount of time becomes infeasible when the problems become large. We present a new nature-inspired approximation algorithm based on the Particle Mechanics (PM) model to compute in parallel approximate efficient solutions for LBPs. Just like other Nature-inspired Algorithms (NAs) drawing from observations of physical processes that occur in nature, the PM algorithm is inspired by physical models of particle kinematics and dynamics. The PM algorithm maps the classical LBP to the movement of particles in a force field by a corresponding mathematical model in which all particles move according to certain defined rules until reaching a stable state. By anti-mapping the stable state, the solution to LBP can be obtained. © 2008 IEEE. | en_US |
dc.language | eng | en_US |
dc.relation.ispartof | 2008 11th IEEE Singapore International Conference on Communication Systems, ICCS 2008 | en_US |
dc.subject | Approximation Algorithm | en_US |
dc.subject | Distributed And Parallel Algorithm | en_US |
dc.subject | Load Balancing | en_US |
dc.subject | Nature-Inspired Algorithm | en_US |
dc.subject | Particle Mechanics Model | en_US |
dc.title | A new nature-inspired algorithm for load balancing | en_US |
dc.type | Conference_Paper | en_US |
dc.identifier.email | Lau, FCM:fcmlau@cs.hku.hk | en_US |
dc.identifier.authority | Lau, FCM=rp00221 | en_US |
dc.description.nature | link_to_subscribed_fulltext | en_US |
dc.identifier.doi | 10.1109/ICCS.2008.4737190 | en_US |
dc.identifier.scopus | eid_2-s2.0-62949187444 | en_US |
dc.relation.references | http://www.scopus.com/mlt/select.url?eid=2-s2.0-62949187444&selection=ref&src=s&origin=recordpage | en_US |
dc.identifier.spage | 289 | en_US |
dc.identifier.epage | 293 | en_US |
dc.identifier.scopusauthorid | Feng, X=55200149100 | en_US |
dc.identifier.scopusauthorid | Lau, FCM=7102749723 | en_US |
dc.identifier.scopusauthorid | Shuai, D=7003359432 | en_US |