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The Computer Journal Advance Access originally published online on October 21, 2008
The Computer Journal 2009 52(8):938-949; doi:10.1093/comjnl/bxn053
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© The Author 2008. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

This article appears in the following The Computer Journal issue: Incorporating Systems, communications and services in smart homes and Software engineering for e-business Special Issues [View the issue table of contents]

Optimizing Access Point Allocation Using Genetic Algorithmic Approach for Smart Home Environments1

Jong-Hyouk Lee1, Byung-Jin Han1, Hyung-Jin Lim2,*, Yeong-Deok Kim3, Navrati Saxena4 and Tai-Myoung Chung1

1 Internet Management Technology Laboratory, Sungkyunkwan University, Korea
2 Korea Financial Security Agency, Korea
3 Department of Computer Information Science and Engineering, Woosong University, Korea
4 School of Information and Communication Engineering, Sungkyunkwan University, Korea

* Corresponding author: hjlim{at}fsa.or.kr

Received 30 January 2008; revised 19 June 2008

In recent years, high-bandwidth and low-cost wireless technologies have emerged as a competitive element, enabling the smart home environment. On the other hand, with the increasing demands for various services, the current access point allocation schemes give rise to significant challenges for a stable connection service, bandwidth and load distribution. In this paper, we present an optimal access point allocation scheme based on genetic algorithm that attempts to optimize multiple parameters, such as bandwidth, and load-balancing requirements. The proposed allocation scheme provides a set of approximately efficient solutions, which allows a wireless user to choose an access point based on its capacity and load balancing, not only regarding its signaling strength or service set identifier. The simulation results are provided to demonstrate the impact of the proposed optimization procedure on overall system performance in terms of connection distribution, load balancing and call dropping probability.

Key Words: optimal access point • genetic algorithm • quality of service • connection distribution • load balancing • call dropping probability • wireless networks

1 Portions of this paper have appeared in Proceedings of International Conference on Future Generation Communication and Networking (FGCN) 2007.


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