Research on resource scheduling of cloud based on improved particle swarm optimization algorithm

Authors:
Yan Wang;Jinkuan Wang;Cuirong Wang;Xin Song
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China;College of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
BICS'13 Proceedings of the 6th international conference on Advances in Brain Inspired Cognitive Systems
Year:
2013

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Abstract

Resource of cloud computing has the characteristics of dynamic, distribution, complexity. How to have the effective scheduling according to the users' QoS (Quality of Service) demand and in order to maximize the benefits is the challenge encountered in cloud computing resource allocation. In this paper, according to the characteristics of the resources of cloud computing, considering the constraints of time and budget needs of users, we designed the scheduling model of resource based on particle swarm optimization algorithm, and used the IPSO (Improved Particle Swarm Optimization algorithm) for global search to obtain the multi-objective optimization solutions that satisfies the requirements. Experimental results show that: when the IPSO applied to the resource of cloud computing compares with other algorithms, it has faster response time and could take efficient use of resource to meet the users' QoS requirements in solving multi-objective problems.