Biologically Inspired Networks: On Energy Efficient Event-Driven Data Collection for Wireless Sensor Networks

Inspired by the nature, the interesting properties of natural organisms can be imitated in many different applications. The nature has been optimizing itself for billions of years and in many cases it simply introduces the most optimal approaches. On the other hand, the task of data collection and aggregation is critical in wireless sensor networks (WSN). The information packets should traverse the network towards the aggregating center i.e. sink node. The problem of finding the best path to route the data has been long under investigation. The authors propose a new method for collecting the data from sensor field based on a biological inspired method adopted from tubular network formation behavior of slime mold where biological organisms efficiently self-organize unreliable and dynamically changing topology, to compensate for the failure of individual components while not relying on explicit central coordination. They show that the emergent network exhibits a widely observed property in natural topologies called scale-free which explains a lot of inherent characteristics in living creatures. At the end the authors show that the data collection time for a biologically inspired network is shorter than uniform channel capacity scheduling.