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Mobile Information Systems
Volume 2017, Article ID 8342859, 10 pages
https://doi.org/10.1155/2017/8342859
Research Article

A Location-Aware Service Deployment Algorithm Based on K-Means for Cloudlets

Department of Electrical Engineering, National Kaohsiung University of Applied Sciences, No. 415, Jiangong Rd., Sanmin Dist., Kaohsiung City 807, Taiwan

Correspondence should be addressed to Tyng-Yeu Liang; wt.ude.sauk.ee.liam@ytl

Received 4 October 2016; Accepted 28 November 2016; Published 9 January 2017

Academic Editor: Jose Juan Pazos-Arias

Copyright © 2017 Tyng-Yeu Liang and You-Jie Li. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Cloudlet recently was proposed to push data centers towards network edges for reducing the network latency of delivering cloud services to mobile devices. For the sake of user mobility, it is necessary to deploy and hand off services anytime anywhere for achieving the minimal network latency for users’ service requests. However, the cost of this solution usually is too high for service providers and is not effective for resource exploitation. To resolve this problem, we propose a location-aware service deployment algorithm based on K-means for cloudlets in this paper. Simply speaking, the proposed algorithm divides mobile devices into a number of device clusters according to the geographical location of mobile devices and then deploys service instances onto the edge cloud servers nearest to the centers of device clusters. Our performance evaluation has shown that the proposed algorithm can effectively reduce not only the network latency of edge cloud services but also the number of service instances used for satisfying the condition of tolerable network latency.