Workflow Scheduling in Cloud Using Nature Inspired Optimization Algorithms

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Amit Chhabra

Abstract

Cloud computing is one of the fastest growing technologies in the world. In the cloud computing scenario, selecting and assigning resource from a large pool of resources to workflow tasks is difficult and known NP-hard problem. Metaheuristics are used to provide near optimal solution to resource assignment problem in cloud and distributed computing systems. In this paper we have presented a survey of variety of meta-heuristic approaches such as genetic algorithm, particle swarm optimization, ant colony optimization, Cat Swarm, Bat, firefly and Grey Wolf Optimizer algorithms which are used for workflow scheduling in cloud environment.

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