Predictive methods for improved vehicular WiFi access

  • Authors:

  • Pralhad Deshpande;Anand Kashyap;Chul Sung;Samir R. Das

  • Affiliations:

  • Stony Brook University, Stony Brook, NY, USA;Symantec Corporatin, Mountain View, CA, USA;Stony Brook University, Stony Brook, NY, USA;Stony Brook University, Stony Brook, NY, USA

  • Venue:
  • Proceedings of the 7th international conference on Mobile systems, applications, and services
  • Year:
  • 2009

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Abstract

With the proliferation of WiFi technology, many WiFi networks are accessible from vehicles on the road making vehicular WiFi access realistic. However, several challenges exist: long latency to establish connection to a WiFi access point (AP), lossy link performance, and frequent disconnections due to mobility. We argue that people drive on familiar routes frequently, and thus the mobility and connectivity related information along their drives can be predicted with good accuracy using historical information - such as GPS tracks with timestamps, RF fingerprints, and link and network-layer addresses of visible APs. We exploit such information to develop new handoff and data transfer strategies. The handoff strategy reduces the connection establishment latency and also uses pre-scripted handoffs triggered by change in vehicle location. The data transfer strategy speeds up download performance by using prefetching on the APs yet to be encountered. Experimental performance evaluation reveals that the predictability of mobility and connectivity is high enough to be useful in such protocols. In our experiments with a vehicular client accessing road-side APs, the handoff strategy improves download performance by roughly a factor of 2 relative to the state-of-the-art. The data transfer strategy further improves this performance by another factor of 2.5.