On efficient neighbor sensing in vehicular networks

Authors:
Zuoxiang Deng;Yanmin Zhu;Minglu Li
Affiliations:
Department of Computer Science and Engineering, Shanghai Jiao Tong University, Dongchuan Road No. 800, Minhang District, Shanghai 200240, PR China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Dongchuan Road No. 800, Minhang District, Shanghai 200240, PR China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Dongchuan Road No. 800, Minhang District, Shanghai 200240, PR China and Shanghai Key Laboratory of Scalable Computing ...
Venue:
Computer Communications
Year:
2012

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Abstract

Efficient neighbor sensing in vehicular wireless networks is crucial to a number of applications such as driving safety and data delivery. For neighbor sensing, a vehicle has to send probe messages. The characteristics of vehicular networks raise several great challenges for real-time neighbor sensing. First, simultaneous wireless transmissions lead to packet collision. The aggressiveness of probe message transmission has a great impact on sensing latency, and it is difficult to determine the optimal aggressive degree of probe message transmission. Second, the number of neighbors of a vehicle in an urban environment may change over time and a static control method for probe message transmission results in poor performance. We design a protocol ENS for efficient neighbor sensing, in which each vehicle performs a randomized broadcast of probe messages in fix-length frames. To approach optimal neighbor sensing, ENS adopts an adaptive probe message transmission strategy. Based on an analytical framework, we theoretically determine the optimal configurations for number of probe messages and frame length. We have conducted trace driven simulation experiments, and performance results demonstrate that ENS outperforms two other alternative algorithms. In addition, more than 90% of association latencies are less than 600ms, and more than 90% of disassociation latencies are less than 200ms under a typical urban setting.