Efficient uncertainty-aware deployment algorithms for wireless sensor networks

Deployment is a fundamental issue in wireless sensor networks. Usually the sensor locations are precomputed based on a "perfect" sensor coverage model, whereas sensors may not always provide reliable information, either due to operational tolerance levels or environmental factors. Therefore, it is imperative to have practical considerations at the design stage to anticipate this sensing behavior. In this paper, we address four different forms of static wireless sensor networks deployment while considering an evidence-based sensor coverage model. The four problems are formalized as combinatorial optimization problems, which are NP-complete. We propose, E2BDA (Efficient Evidence-Based sensor Deployment Algorithm), a polynomial-time uncertainty-aware deployment algorithm based on a dynamic programming approach. E2BDA is able to determine the minimum number of sensors and their locations to achieve both coverage and connectivity. We compare our proposal to the state-of-the-art deployment strategies, the obtained results show that E2BDA obtains the best performances.