Self-stopping strategies for tractable information dissemination in dense mobile sensor networks

Abstract

This paper studies a new epidemic routing problem: disseminating the information to a certain percentage of nodes in the network in a timely and predictable manner, and suppressing further spreading when the goal has been reached. We apply an accurate mathematical model to analyse and design different distributed self-stopping strategies on information dissemination in dense wireless mobile sensor networks. The probability-based self-stopping strategy adjusts the stopping probability to subdue message forwarding when a sensor node meets a neighbour already informed. Such a strategy can reach the percentage goal accurately, but does not stop timely and cannot control the dissemination under 82%. Using the message life time as a guideline, we propose two new selfstopping strategies by either setting a hop count limit or adopting a final forwarding probability. Such strategies not only stop fast and save energy, but also control the scope of message spreading to an arbitrary goal.