A Hybrid Swarm Particle Optimization Algorithm for Task Scheduling in Cloud Computing

Ehram Safari, Seyedeh OmSalameh Pourhashemi, Mohsen Gharahkhani


Today, cloud computing experts seek internet-based service providing to share resources using service providing techniques. This environment provides users with an image of abundant resources. The present paper recommends a combination of particle swarm optimization algorithm and simulated annealing algorithm to obtain an improvement in the performance of task scheduling to resources considering the available bandwidth allocated to each virtual machine. The performance of the proposed algorithm is investigated by the use of the Cloudsim Simulator. Research results show that the proposed algorithm outperforms the Swarm Particle Optimization (SPO), bat, and raven roosting optimism algorithms in terms of task execution time, response time, and performance efficiency.


Cloud computing, Cloudsim Simulator, Swarm Particle Optimization, Efficiency, Task scheduling

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