Probabilistic path selection in wireless sensor networks with controlled mobility
Xiwei Zhang, Lili Zhang, Guihai Chen, Xia Zou · 2009
We consider the problem of planning path of a ¿data mule¿ in a cluster based sensor networks. Recent research shows that significant energy saving can be achieved by using this mobile data collection nodes. Although a data mule (DM) can reduce the energy consumption of the cluster head (CH), it increases the latency from the time the CH gain the data to the time the base station receives it. To address this issue, we propose a dynamic data mule path selection algorithm which called probabilistic path selection (PPS). In surveillance sensor networks, sensor nodes transmit data to CH only when event is detected. Some clusters which did not detect the event would have no data to transmit for power consumption. In this circumstance, DM ignores these CHs to shorten the length of path. The PPS algorithm can reselect the path based on the probability of CH obtaining data. The simulation shows that our algorithm can significantly reduce the data latency and satisfy the user's delay requirement simultaneously.