ANTS: Efficient Vehicle Locating Based on Ant Search in ShanghaiGrid

Authors:
Hongzi Zhu;Yanmin Zhu;Minglu Li;Lionel M. Ni
Affiliations:
Shanghai Jiao Tong University, China;Hong Kong University of Science and Technology, Hong Kong;Shanghai Jiao Tong University, China;Shanghai Jiao Tong University, China/ Hong Kong University of Science and Technology, Hong Kong
Venue:
ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
Year:
2007

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Abstract

Intelligent transportation systems have become increasingly important for the public transportation in Shanghai. In response, ShanghaiGrid aims to provide abundant intelligent transportation services to improve the traffic condition. A fundamental service in ShanghaiGrid is to locate the nearest desirable vehicles for users. In this paper we propose an innovative protocol ANTS to locate a desirable vehicle close to the querying user. The protocol finely mimics the efficient searching strategy adopted by a lost desert ant in searching for its nest. Taking query locality into account, ANTS can retrieve the nearest vehicles satisfying the query with high probability but incurs small query latency and modest network traffic. ANTS is a fully distributed and robust protocol and therefore has good scalability. Extensive simulations based on the real road network and the trace data of vehicle movements in Shanghai demonstrate the efficacy of ANTS.