Comparative Analysis of Evolutionary Algorithms Based on Swarm Intelligence for QoS Optimization of Cloud Services
The authors wish to thank Natural Science Foundation of China under Grant NO. 61662054, 61262082, Research Program of science and technology at Universities of Inner Mongolia Autonomous Region Grant NO. NJZY008, Inner Mongolia Science and technology innovation team of Cloud Computing and Software Engineering, Inner Mongolia Application Technology Research and Development Funding Project under Grant NO. 201702168, CERNET Innovation Project under Grand No.NGII20160511, Inner Mongolia Engineering Lab of Cloud Computing and Service Software and Inner Mongolia Engineering Lab of Big Data Analysis Technology.
IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD)
As the technology of cloud computing becomes mature, the service idea of IT resources has been promoted rapidly. The various available cloud services have different quality of service (QoS). Different users have different QoS requirements for services. Finding the best QoS strategy which a user is satisfied with is a multi-criteria NP-hard problem. The completed theory and applied research have proved that the swarm intelligence method can effectively solve most multiobjective optimization problems. Therefore, a Pareto optimal solution for QoS strategy can be found by an evolutionary algorithm based on swarm intelligence. However, so far, only few solutions based on these approaches have been proposed and there exists no comparative study published to date. This motivated us to perform an analysis of state of the art evolutionary algorithm based on swarm intelligence. By a large number of contrast experiments under different circumstances, three QoS evolutionary algorithms based on swarm intelligence are analyzed and compared.
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Wang, Y., Zhou, J. T., Jiao, Y., & Song, X. (2019, May). Comparative Analysis of Evolutionary Algorithms Based on Swarm Intelligence for QoS Optimization of Cloud Services. In 2019 IEEE 23rd International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 434-439). IEEE.