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An approach to building energy clusters using particle swarm optimization algorithm for allocating the tasks in computational grid

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cris.author.scopus-author-id 58826747800
cris.author.scopus-author-id 55633508000
cris.author.scopus-author-id 57194844651
cris.author.scopus-author-id 57207470375
cris.author.scopus-author-id 57195514183
cris.author.scopus-author-id 24824279500
dc.contributor.author Islam R.
dc.contributor.author Akhtar M.N.
dc.contributor.author Ahmad B.R.
dc.contributor.author Das U.K.
dc.contributor.author Rahman M.
dc.contributor.author Khalib Z.I.A.
dc.date.accessioned 2024-12-12T08:41:50Z
dc.date.available 2024-12-12T08:41:50Z
dc.date.issued 2019-05-01
dc.description.abstract The proper mapping in case of allocation of available tasks among particles is a challenging job to accomplish. It requires proper procedural approach and effectual algorithm or strategy. The deterministic polynomial time for task allocation problem is relative. The existence of proper and exact approach for allocation problem is void. However, for the survival of the grid and executing the assigned tasks, the reserved tasks need to be allocated equally among the particles of the grid space. At the same time, the applied model for task allocation must not consume unnecessary time and memory. We applied Particle Swarm Optimization (PSO) for allocating the task. Additionally, the particles will be divided into three clusters based on their energy level. Each cluster will have its own cluster header. Cluster headers will be used to search the task into space. In a single cluster, particles member will be of same energy level status such as full energy, half energy, and no energy level. As a result, the system will use the limited time for searching task for the remaining tasks in it if a particular task requires allocating half task to a particle.
dc.identifier.doi 10.11591/ijeecs.v14.i2.pp826-833
dc.identifier.scopus 2-s2.0-85062522565
dc.identifier.uri https://hdl.handle.net/20.500.14170/10261
dc.relation.grantno undefined
dc.relation.ispartof Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.ispartofseries Indonesian Journal of Electrical Engineering and Computer Science
dc.relation.issn 25024752
dc.rights open access
dc.subject Computational grid | Energy cluster | Energy cluster header | Particle swarm optimization
dc.title An approach to building energy clusters using particle swarm optimization algorithm for allocating the tasks in computational grid
dc.type Journal
dspace.entity.type Publication
oaire.citation.endPage 833
oaire.citation.issue 2
oaire.citation.startPage 826
oaire.citation.volume 14
oairecerif.affiliation.orgunit International University of Business Agriculture and Technology
oairecerif.affiliation.orgunit Dhaka University of Engineering and Technology, Gazipur
oairecerif.affiliation.orgunit Universiti Sultan Zainal Abidin
oairecerif.affiliation.orgunit International University of Business Agriculture and Technology
oairecerif.affiliation.orgunit Daffodil International University
oairecerif.affiliation.orgunit Universiti Malaysia Perlis
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person.identifier.scopus-author-id 58826747800
person.identifier.scopus-author-id 55633508000
person.identifier.scopus-author-id 57194844651
person.identifier.scopus-author-id 57207470375
person.identifier.scopus-author-id 57195514183
person.identifier.scopus-author-id 24824279500
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