Energy Consumption Optimization for Data Collection with Precision Constraints in Wireless Sensor Networks

Optimizing network energy consumption is one of the most important issues in wireless sensor networks (WSNs). In this work we consider the energy consumption optimization problem for data collection applications. The network energy consumption can be reduced by letting a subset of sensors go into energy saving sleep state. However, the cost of the energy saving is the loss of observation precision. Given the application precision constraints, we try to select a suitable set of reporters and relays such that the network energy consumption is optimized while the precision constrains are satisfied. We formulate the problem as a PCEO problem and give a binary integer linear programming (BILP) formulation for the problem. The linear programming (LP) extension of the BILP problem can provide a lower bound for the PCEO problem. The PCEO problem is shown to be NP-complete and three greedy heuristics are developed for it. The performance of the heuristics is studied through extensive simulations and compared with the lower bound by solving LP.