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Cloud computing is a subscription-based service whose primary benefit is application scalability which allows realtime provisioning of resources to meet application requirements. Scheduling is the most prominent issue in cloud computing. Generally the goal of scheduling is to properly dispatch parallel jobs to slave node machines according to different scheduling policies. In this paper previously existing algorithms i.e. Particle Swarm Optimization (PSO), Improved Particle Swarm Optimization (IPSO), Simulated Annealing (SA) Algorithm, and Hybrid Particle Swarm OptimizationSimulated Annealing based on utilization time are studied which were proposed to handle problems posed by network properties between user and resources. A new algorithm is designed using shortest path theory, Particle Swarm Optimization and Simulated Annealing technique which achieve the target consuming less average execution time to obtain more efficiency in resource utilization and minimize the cost of the processing.

An Upgraded Algorithm of Resource Scheduling using PSO and SA in Cloud Computing