An efficient mobility prediction model for resource allocation in mobile cloud computing

Article type: Research Article

Authors: Akki, Praveena | Vijayarajan, V.^*

Affiliations: School of Computer Science and Engineering, Vellore, Tamil Nadu, India

Correspondence: [*] Corresponding author: V. Vijayarajan, School of Computer Science and Engineering, Vellore 632014, Tamil Nadu, India. Tel.: +91 416 224 3091; Fax: +91 416 224 3092; E-mail: vijayarajan.v@vit.ac.in.

Abstract: Mobile cloud computing (MCC) is a technology which provides cloud server resources to mobile users with optimized latency. MCC allows mobile device to access cloud resources and to offload tasks to cloud let servers at any time and from anywhere. The cloud let servers are attached to wireless Access points. But mobility plays an important role which leads to the loss of connectivity of mobile devices because of varying signal strengths. On the other hand, optimal code execution is a challenge. In this paper, a connectivity base mobility prediction method is proposed to assign the cloud resources to the user without loss in the connection. The past accessing history of the users and path loss factors are taken into consideration to predict proper access point. From the performance evaluation the performance of the proposed method is increased by 15.23% when compared to other existing methods.

Keywords: Signal strength, path loss, Shadowing, mobility patterns, execution time, access points

DOI: 10.3233/KES-210060

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 25, no. 1, pp. 149-157, 2021