Near-optimal online algorithm for data collection by multiple sinks in wireless sensor networks

Data collection by multiple sinks is a fundamental problem in wireless sensor networks. Existing work focused on designing optimal offline algorithms provided that the number and positions of sensors and sinks are predetermined. This may not be practical as, though sensors are cheap, sinks are quite expensive in reality. A more practical scenario is that sinks are deployed step by step during the network operation due to the budget constraint, and we do not know the number, positions and capacities of sinks in prior. In this paper we investigate such an optimal data collection problem by multiple sinks, and design a near-optimal online algorithm via primal-dual approach, requiring very little priori knowledge. We theoretically derive the competitive ratio and show how to improve it by finding the optimal sink location region with an approximation ratio. Extensive simulations are conducted to verify the performance of the proposed online algorithm.