چکیده مقاله
Cloud computing is a technology in which shared resources networks, servers, storage locations, applications and services are available through an extensive and dynamic network, and the cloud user can get access to it as quickly as possible and at the lowest cost In this paper, a scheduling method based on particle swarm optimization PSO is presented so that it can be used to establish a trade off between various quality of service parameters whileoptimally allocating the resources and properly making a load balance The proposed technique prevents overloading and under loading servers by optimally assigning tasks to processing servers Also, servers that are overloaded and in other words congested, their tasks are transferred to other servers by live migration of the virtual machines It provides increasing in cloud infrastructure load balancing and thus the execution time of tasks are significantlyreduced The proposed method was compared with two Ant Colony Optimization ACO and Round Robin RR algorithm and it is shown that the proposed method is able to execute the desired requests in less time versus two algorithms It is resulted by using the multi objective PSO algorithm and the correct migrations that the proposed technique is provided By using this method, it is made a trade off among various quality of service parameters involvedresponse time, energy consumption and degradation of the service level agreement
کلیدواژهها
نویسندگان
Ali Bazghandi
Faculty of Computer Engineering & IT of Shahrood University of Technology, Iran
Mostafa Bazghandi
Faculty of Computer Engineering of Islamic Azad University of Sabzevar, Iran
شیوه ارجاع
Bazghandi, Ali and Bazghandi, Mostafa,1400,A Multi-objective PSO based method for Task Scheduling in Cloud Computing,Fourth International Conference on Soft Computing
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