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Context-aware and location-based service discovery protocol for vehicular networks

Published:28 October 2009Publication History

ABSTRACT

Vehicular Networks (VN) have attracted recent attention from researchers mainly motivated by the potential applications that will leverage Intelligent Transportation Systems (ITS). Such applications include road safety and security, traffic monitoring and driving comfort. However, several research challenges must be overcome before Vehicular Networks can be wide deployed. One of these challenges comprises how vehicles and service providers could discover each other in a Vehicular Networks, which is well-known for its large scale and high-mobility nature. Therefore, existing service discovery techniques for low-mobility or wired networks cannot be applied directly to Vehicular Networks. Most service discovery strategies available present high overhead and poor performance in a Vehicular Network scenario. In this paper, we propose a context-aware and location-based service discovery protocol for next generation Vehicular Networks (LocVSDP). Our protocol offers a scalable framework for the discovery of time-sensitive and location based services in Vehicular Networks. Furthermore, LocVSDP is integrated into the network layer and uses channel diversity for improved service discovery efficiency. We discuss the implementation of our protocol and compare the message and time complexities of our protocol with the existing location-based service discovery protocol VITP. Our results indicate that our techniques outperform the VITP protocol in terms of message and time complexities.

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        cover image ACM Conferences
        PE-WASUN '09: Proceedings of the 6th ACM symposium on Performance evaluation of wireless ad hoc, sensor, and ubiquitous networks
        October 2009
        176 pages
        ISBN:9781605586182
        DOI:10.1145/1641876

        Copyright © 2009 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 28 October 2009

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        Overall Acceptance Rate70of240submissions,29%

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