A Robust Node Selection Strategy for Lifetime Extension in Wireless Sensor Networks

Distributed wireless sensor networks consist of energy-constrained sensor nodes that may be deployed in large numbers in order to monitor a given area. In such densely deployed environments, multiple transmissions can lead to collisions resulting in lost packets and energy wastage due to retransmissions. These networks also feature significant redundancy since nodes close to each other often sense similar data. Therefore, it may be adequate to utilize only a subset of data captured by the network. In this paper, high-energy subsets of the nodes are selected in a manner that coverage and connectivity are consistently achieved. The working subsets are changed over time after predetermined durations. A framework using concepts from spatial statistics is developed as an approach to selecting the subset of sensors. For example, an attempt at determining the correlation distance of a sensor field in the absence of real sensor data is made. Simulation results show that the algorithm is robust and retains certain level of redundancy. The ability of the algorithm to extend network lifetime is shown and the redundancy provided by the subsets selected is analyzed along with the fault tolerance provided. Conclusions regarding the flexibility and application scenarios of the algorithm are drawn.