We propose an algorithm for maximizing the lifetime of a wireless sensor network when there is a mobile sink and the underlying application can tolerate some amount of delay in delivering the data to the sink. The algorithm is distributed, and in addition, mostly uses local information. Such an algorithm can be implemented by parallel and/or distributed execution and the overhead of message passing is low. It is also possible to embed the algorithm into a network protocol so that the sensor nodes and the sink can run it directly as part of the network operation. We give a proof of the algorithm's optimality and the boundedness of the queue sizes, both in the long-run average sense. The proof is based on analyzing a Lyapunov drift.

This paper proposes a framework to maximize the lifetime of the wireless sensor networks (WSNs) by using a mobile sink when the underlying applications tolerate delayed information delivery to the sink. Within a prescribed delay tolerance level, each node does not need to send the data immediately as it becomes available. Instead, the node can store the data temporarily and transmit it when the mobile sink is at the most favorable location for achieving the longest WSN lifetime. To find the best solution within the proposed framework, we formulate optimization problems that maximize the lifetime of the WSN subject to the delay bound constraints, node energy constraints, and flow conservation constraints. We conduct extensive computational experiments on the optimization problems and find that the lifetime can be increased significantly as compared to not only the stationary sink model but also more traditional mobile sink models. We also show that the delay tolerance level does not affect the maximum lifetime of the WSN.