A User Configurable Metric for Clustering in Wireless Sensor Networks

Abstract

Wireless Sensor Networks (WSNs) are comprised of thousands of nodes that are embedded with limited energy resources. Clustering is a well-known technique that can be used to extend the lifetime of such a network. However, user adaption is one criterion that is not taken into account by current clustering algorithms. Here, the term "user" refers to application developer who will adjust their preferences based on the application specific requirements of the service they provide to application users. In this paper, we introduce a novel metric named Communication Distance (ComD), which can be used in clustering algorithms to measure the relative distance between sensors in WSNs. It is tailored by user configuration and its value is computed from real time data. These features allow clustering algorithms based on ComD to adapt to user preferences and dynamic environments. Through experimental and theoretical studies, we seek to deduce a series of formulas to calculate ComD from Time of Flight (ToF), Radio Signal Strength Indicator (RSSI), node density and hop count according to some user profile.