Document Type
Article
Publication Date
4-2011
Publication Title
Wireless Networks
Abstract
The field of wireless networking has received unprecedented attention from the research community during the last decade due to its great potential to create new horizons for communicating beyond the Internet. Wireless LANs (WLANs) based on the IEEE 802.11 standard have become prevalent in public as well as residential areas, and their importance as an enabling technology will continue to grow for future pervasive computing applications. However, as their scale and complexity continue to grow, reducing handoff latency is particularly important. This paper presents the Behavior-based Mobility Prediction scheme to eliminate the scanning overhead incurred in IEEE 802.11 networks. This is achieved by considering not only location information but also group, time-of-day, and duration characteristics of mobile users. This captures short-term and periodic behavior of mobile users to provide accurate next-cell predictions. Our simulation study of a campus network and a municipal wireless network shows that the proposed method improves the next-cell prediction accuracy by 23~43% compared to location-only based schemes and reduces the average handoff delay down to 24~25 ms.
Repository Citation
Wanalertlak, Weetit; Lee, Ben; Yu, Chansu; Kim, Myungchul; Park, Seung-Min; and Kim, Won-Tae, "Behavior-Based Mobility Prediction for Seamless Handoffs in Mobile Wireless Networks" (2011). Electrical and Computer Engineering Faculty Publications. 76.
https://engagedscholarship.csuohio.edu/enece_facpub/76
Original Citation
Weetit, W., Ben, L., Chansu, Y., Myungchul, K., Seung-Min, P., & Won-Tae, K. (2011). Behavior-based mobility prediction for seamless handoffs in mobile wireless networks. Wireless Networks (10220038), 17(3), 645-658. doi:10.1007/s11276-010-0303-x
DOI
10.1007/s11276-010-0303-x
Version
Postprint
Publisher's Statement
The final publication is available at Springer via http://dx.doi.org/10.1007/s11276-010-0303-x
Volume
17
Issue
3
Included in
Digital Communications and Networking Commons, Electrical and Computer Engineering Commons