Self-stopping epidemic routing in cooperative wireless mobile sensor networks

Epidemic routing is considered useful for wireless mobile sensor networks where infrastructure support is limited and sensed information has to be disseminated in a timely manner. The relaying overhead of epidemic routing, however, needs to be reduced to conserve energy. In this paper, we study a new problem: what is a good strategy in epidemic routing to self-stop forwarding a message when a certain percentage of nodes have received a copy of the message? The goal of such a strategy is to disseminate the information to a certain percentage of nodes in the network in a timely and predictable manner, and at the same time to cooperatively avoid further spreading when the goal has been reached. As a first attempt, we focus on wireless mobile sensor networks where nodes move rapidly and randomly around and a synchronous time model is applied. We first select an accurate mathematical model to characterize the information dissemination in wireless mobile sensor networks. We then apply and extend the model to analyze and design different self-stopping strategies. Moreover, we propose a new self-stopping strategy, called the time-based probabilistic self-stopping strategy, by taking advantages of both the time-based and the probability-based strategies. We find that such a self-stopping strategy is fast, accurate, and energy efficient.