Fastest Path in Time Varying Wireless Sensor Networks

Abstract

In wireless sensor networks, sensors usually switch between active and sleeping mode for energy conservation. Considering that different sensors may have different sleep and wakeup scheduling for various monitoring tasks, finding the fastest path from a given sensor to a sink is a time varying problem. To solve this time-varying routing problem, we firstly propose a centralized algorithm to find the shortest path from any sensor node to the sink. To make it more practical, we improve to a progressive routing scheme by combining a centralized routing adjustment algorithm with a distributed greedy routing algorithm. In our work, we firstly build a layer-based model to locate every sensor node. In this way, sensor nodes in the system model can easily find routes through a distributed greedy algorithm. Since this algorithm may not find the shortest path, the sink then executes an optimal adjustment algorithm to adapt the routing choice of sensor nodes on the path and push the greedy path to the optimal path with the minimum cost. An example and some comparisons are reported later to illustrate the effectiveness of the proposed method.