GPSR: greedy perimeter stateless routing for wireless networks
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
MDDV: a mobility-centric data dissemination algorithm for vehicular networks
Proceedings of the 1st ACM international workshop on Vehicular ad hoc networks
Enabling efficient and accurate large-scale simulations of VANETs for vehicular traffic management
Proceedings of the fourth ACM international workshop on Vehicular ad hoc networks
Delay-bounded routing in vehicular ad-hoc networks
Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing
Route lifetime based optimal hop selection in VANETs on highway: an analytical viewpoint
NETWORKING'06 Proceedings of the 5th international IFIP-TC6 conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communications Systems
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Vehicular ad hoc networks (VANETs) allow communications over sequences of vehicles with radio devices. There are many possible applications over a VANET such as traffic jam warning, collision warning, parking lot reservations, camera picture feed, and so forth. There have been quite a few results in the area seeking for a fast and reliable communication protocol due to their potential. VANETs, however, are pointed out as difficult for numerical optimizations due to frequent changes in their topologies. As a result, heuristic methods such as GPSR have been mainly used for routing packets over multihop communications. In this paper, we present an algorithm to precompute the probability that communication is possible between specified source and destination in a VANET, under certain mathematical assumption. The proposed new protocol for multihop communication refers to a lookup table containing the precomputed data to decide a good packet forwarder quickly. We create a simulation testbed that seems challenging for all the existing multihop routing protocols for VANETs, in which we test ours. We seemuch improved performances over GPSR after the algorithm is refined for some practical issues.