Near-lifetime-optimal data collection in wireless sensor networks via spatio-temporal load balancing

In wireless sensor networks, periodic data collection appears in many applications. During data collection, messages from sensor nodes are periodically collected and sent back to a set of base stations for processing. In this article, we present and analyze a near-lifetime-optimal and scalable solution for data collection in stationary wireless sensor networks and an energy-efficient packet exchange mechanism. In our solution, instead of using a fixed network topology, we construct a set of communication topologies and apply each topology to different data collection cycles. We not only use the flexibility in distributing the traffic load across different routes in the network (spatial load balancing), but also balance the energy consumption in the time domain (temporal load balancing). We show that this method achieves an average energy consumption rate very close to the optimal value found by network flow optimization techniques. To increase the scalability, we further extend our solution such that it can be applied to networks with multiple base stations where each base station only stores part of the network configuration, cooperating with each other to find a global solution in a distributed manner. The proposed methods are analyzed and evaluated by simulations.