Abstract: A vehicular ad hoc network is an emerging technology, however some challenging issues need to be resolved. In recent years, road congestion and traffic related pollution have a large negative social and economic impact worldwide. For better public transport, strategic planning, traffic monitoring is required to cut pollution and congestion. One of the important attributes of traffic data is the interval between the time that the data are generated by a vehicle on a particular road and the time that the data is made available to the user as a query response and also to select the fastest route to a destination in a reliable manner. To address these issues, this work focuses on two routing algorithms for VANETS 1) Delay bounded greedy forwarding(D-Greedy) 2)Delay bounded minimum cost forwarding (D-MinCost). The first proposed algorithm (D-Greedy) exploits local traffic conditions, i.e., information about the speed and density of cars at the road segment that it currently traverses. The second algorithm (D-MinCost) assumes knowledge of global traffic conditions, i.e., statistical information about the speed and density of cars on every road segment of the city. This work explores on the current traffic conditions on that road segment. Also a framework is proposed for vehicular networks that jointly optimizes the two key processes associated with monitoring traffic i.e. data acquisition and data delivery.
Keywords: Ad hoc network, data muling (DM), multihop (MH) communication, routing, sensor participation, traffic monitoring, vehicular ad hoc networks (VANETs), vehicular networks.
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