Constrained Flow Optimization with Applications to Data Gathering in Sensor Networks

We focus on data gathering problems in energy-constrained wireless sensor networks. We study store-and-gather problems where data are locally stored on the sensors before the data gathering starts, and continuous sensing and gathering problems that model time critical applications. We show that these problems reduce to maximization of network flow under vertex capacity constraint, which reduces to a standard network flow problem. We develop a distributed and adaptive algorithm to optimize data gathering. This algorithm leads to a simple protocol that coordinates the sensor nodes in the system. Our approach provides a unified framework to study a variety of data gathering problems in sensor networks. The efficiency of the proposed method is illustrated through simulations.