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- W2767215200 abstract "The main objective of virtual distributed computing is optimization of load in an efficient manner. This is achieved using load scheduling in cloud computing. The cloud is a virtual distributed environment having a huge set of resources. It offers us an incremental paradigm to obtain effective data transfer among the virtual machines and cloudlets. The paper proposes New Particle Search Optimization (NPSO) based load scheduling approach to obtain cost minimization by processing the cloudlets on VMs. It specifies a meta-heuristic swarm intelligence based approach by storing the best positions. The swarm of particles affects the behavior of the cloudlets. This is achieved using a new cost evaluation function. This paper analyzes the particle swarm optimization and NPSO (New Particle Search Optimization) on a large data set of cloudlets and VMs. The proposed approach provides higher efficiency by cost optimization (minimized cost) based on the statistical analysis of the total cost (execution and transfer) on a data set of number of iterations and particles." @default.
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- W2767215200 date "2017-01-01" @default.
- W2767215200 modified "2023-09-26" @default.
- W2767215200 title "NPSO Based Cost Optimization for Load Scheduling in Cloud Computing" @default.
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- W2767215200 doi "https://doi.org/10.1007/978-981-10-6898-0_9" @default.
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