Title: A study of situation awareness-based resource management scheme in cloud environment

Authors: Junshe Wang; Zheng Li; Hongbin Zhang; Yuzi Yi

Addresses: Institution: School of Information Science and Engineering, Hebei University of Science and Technology, 26 Yuxiang St, Yuhua Qu, Shijiazhuang Shi, Hebei Sheng, China ' Institution: School of Information Science and Engineering, Hebei University of Science and Technology, 26 Yuxiang St, Yuhua Qu, Shijiazhuang Shi, Hebei Sheng, China ' Institution: School of Information Science and Engineering, Hebei University of Science and Technology, 26 Yuxiang St, Yuhua Qu, Shijiazhuang Shi, Hebei Sheng, China ' Institution: School of Information Science and Engineering, Hebei University of Science and Technology, 26 Yuxiang St, Yuhua Qu, Shijiazhuang Shi, Hebei Sheng, China

Abstract: In view of the defects of the current cloud resource management, which results in low utilisation of resources. This paper proposes a new method for the cloud environment, which is based on situation awareness. Meanwhile it is particularly important to collect historical load data of resources in the process of situation awareness. In order to improve the quality of data acquisition and reduce the burden of the data collection system, a new adaptive data acquisition algorithm is also designed. The proposed scheme comprehensively evaluates the current situation of the use of resources using FAHP (fuzzy analytic hierarchy process). Meanwhile, the cycle of data acquisition is adjusted in real-time, according to the result of resource evaluation. Then, in order to improve the utilisation of resources and achieve its efficient use, the improved BP algorithm is used to forecast the resource requirement of the next time which can provide the basis for rational allocation.

Keywords: cloud computing; resource requirement; situation awareness; adaptive data acquisition.

DOI: 10.1504/IJCNDS.2020.104761

International Journal of Communication Networks and Distributed Systems, 2020 Vol.24 No.2, pp.214 - 232

Received: 12 Jun 2018
Accepted: 28 Sep 2018
Published online: 30 Jan 2020 *

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