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A New Hybrid Particle Swarm Optimizationalgorithm for Optimal Tasks Scheduling in Distributed Computing System by Karishma; Harendra Kumar is a Computer Science article available to read on EtoBox.

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Tasks allocation problem in heterogeneous and distributed-multiprocessing computing environments is a nonlinear multi-objective NP-hard problem and from a research perspective, it is considereda major issue. The underlying objective of any allocation mechanism to execute the specified tasks set and enumerating processors is to minimize the overall cost. To solve the tasks allocation problems numerous meta-heuristic techniques have been tried and tested but still, plenty of scopes are there for optimal strategies. In the presented article, a comprehensive task assignment model based on particle swarm optimization (PSO) is developed, which optimizes response time, flowtime, and cost of the distributed computing system. In the present technique, the ‘n’ number of cluster centroids of ‘r’ tasks, is updated by the PSO technique to form the ‘n’ task clusters to minimize the communication costs then their allocation is made by the newly proposed heuristic method. Considering the fact, in the given model objective functions conflict with each other and the good thing about the PSO algorithm are its accuracy and speed. And to come up with the most favorable solution, authors have developed

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Author

Karishma; Harendra Kumar

Publisher

Elsevier BV

Published

2023

Language

EN

Field

Computer Science (Physical Sciences)