Resource scheduling strategy for uncertain factors in mobile cloud computing

Issue title: Artificial Intelligence and Advanced Manufacturing (AIAM 2020)

Guest editors: Shengzong Zhou

Article type: Research Article

Authors: Chen, Ying^{a; b; *}

Affiliations: [a] Jiyang College of Zhejiang A&F University, China | [b] Department of Computer Science and Technology, Nanjing University, China

Correspondence: [*] Corresponding author. Ying Chen, E-mail: [email protected].

Abstract: At present, resource configuration of mobile cloud computing has received extensive attention from the outside world. Most of the similar resource scheduling configuration fails to comprehensively consider the dynamics of mobile terminals and the difference in user requested resources. Therefore, considering uncertainty in paging scheduling under mobile cloud resource environment from the perspective of consumers has become the key to solving the problem of resource allocation in the mobile cloud computing environment. This paper proposes an adaptive matching resource allocation algorithm based on uncertain factors under mobile cloud computing environment. Uncertain factors of the mobile terminal are derived via QoS attribute, and then user information and load characteristics of the user requested resources are analyzed through CLIQUE similarity matching. Afterwards, based on the mapping between similarity and resources, resource paging allocation can be carried out based on adaptive matching resource allocation algorithm. From the perspective of consumers, dynamics of mobile terminals and uncertainty of paging scheduling in the mobile cloud resource environment under different user requested resources can be considered to allow minimized delay and optimized paging strategies.

Keywords: Mobile cloud computing, uncertain factors, resource scheduling, paging strategy

DOI: 10.3233/JIFS-189716

Journal: Journal of Intelligent & Fuzzy Systems, vol. 41, no. 3, pp. 4559-4564, 2021