The Research on Resource Scheduling Based on Fuzzy Clustering in Cloud Computing

TLDR: The experimental results show that job scheduling strategy based on CBFCM resources classification in the cloud computing services have certain advantages and AFCFS job scheduling algorithm in average response time for ART, the average waiting time AWT, average operating cost of ACP performance items, has great advantage than the other three algorithm.

Abstract: In this paper, the assignment performance problem in the process of the allocation resources has not been considered in the present most cloud computing data center, this paper proposes a new cloud computing resources allocation strategy, on the basis of cost model of the parallel task performance, using the improved Fuzzy Clustering Algorithm (CBFCM -- C Cost based Fuzzy Clustering Algorithm) to classify the cloud computing resources set on the service level of user, and the jobs submitted by guest were analyzed using four different scheduling algorithms, and the generated resource scheduling scheme. The experimental results show that job scheduling strategy based on CBFCM resources classification in the cloud computing services have certain advantages. AFCFS job scheduling algorithm in average response time for ART, the average waiting time AWT, average operating cost of ACP performance items, has great advantage than the other three algorithm.