Behavior-based mobility prediction for seamless handoffs in mobile wireless networks

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 shortterm and periodic behavior of mobile users to provide Weetit Wanalertlak and Ben Lee School of Electrical Engineering and Computer Science Oregon State University Corvallis, OR 97330, USA E-mail: {wanalewe, benl}@eecs.orst.edu Chansu Yu Dept. of Electrical and Computer Engineering Cleveland State University Cleveland, OH 44115, USA E-mail: [email protected] Myungchul Kim Korea Advanced Institute of Science and Technology 335 Gwahangno, Yuseong-gu, Daejeon 305-714 Republic of Korea E-mail: [email protected] Seung-Min Park and Won-Tae Kim Embedded Software Research Division Electronics and Telecommunications Research Institute 138 Gajeongno, Yuseong-gu, Daejeon 305-700 Republic of Korea E-mail: {minpar, kwtkim}@etri.re.kr 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 locationonly based schemes and reduces the average handoff delay down to 24∼25 ms.