Abstract
Vehicles can provide useful data to many urban computing applications. This paper addresses the issue of collecting data from multiple vehicles to a roadside base station using VANET. The impacts of real-time traffic condition have not been widely discussed in literature. In this paper, we study the data collection problem under different traffic conditions. The objective is to minimize the network communication overhead while satisfying the data collection time constraint. We formulate the problem as an scheduling optimization problem. A dynamic programming based solution and a genetic algorithm based solution are developed to solve the problem for different application scenarios. The solution can adaptively choose to carry or forward data based on current traffic information. Evaluation shows that the proposed solution outperforms some existing ones in terms of effectiveness and efficiency.
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