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

  • Authors:
  • Weetit Wanalertlak;Ben Lee;Chansu Yu;Myungchul Kim;Seung-Min Park;Won-Tae Kim

  • Affiliations:
  • School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, USA 97331;School of Electrical Engineering and Computer Science, Oregon State University, Corvallis, USA 97331;Department of Electrical and Computer Engineering, Cleveland State University, Cleveland, USA 44115;Korea Advanced Institute of Science and Technology, Yuseong-gu, Korea 305-701;Embedded Software Research Division, Electronics and Telecommunications Research Institute, Yuseong-gu, Korea 305-700;Embedded Software Research Division, Electronics and Telecommunications Research Institute, Yuseong-gu, Korea 305-700

  • Venue:
  • Wireless Networks
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

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.