Title: Cluster analysis algorithm based on key data integration for cloud computing
Authors: Li Dong-rui
Addresses: Department of Computer, Guangdong AIB Polytechnic College, 510507, Guangzhou, China
Abstract: In order to improve scheduling efficiency and a kind of cloud task scheduling algorithm of improved fuzzy cluster has been proposed. Firstly, cloud task scheduling algorithm of improved fuzzy cluster has been introduced, which mainly uses fuzzy FCM algorithm to complete resource cluster to three resource sets including computing type, storage type and bandwidth type in the context of using parallel processing to ensure the efficiency. The resource of cluster set with the longest time in completion will be liberated from the busy schedule to improve the utilisation ratio of resources, ensure load balance, reduce execution costs and enhance customer satisfaction; secondly, tasks have been allocated to each cluster through Min-Min heuristic algorithm and the results have been adjusted according to set threshold to obtain the better scheduling results. The experimental results show that the proposed algorithm is superior to the traditional algorithm without cluster in terms of execution time.
Keywords: big data; cloud computing; approximate data; fuzzy cluster; resource scheduling; intelligent algorithm.
International Journal of Reasoning-based Intelligent Systems, 2017 Vol.9 No.3/4, pp.123 - 129
Received: 11 May 2017
Accepted: 07 Jun 2017
Published online: 27 Feb 2018 *