Fuzzy decision making through energy-aware and utility agents within wireless sensor networks

Multi-agent systems (MAS) through their intrinsically distributed nature offer a promising software modelling and implementation framework for wireless sensor network (WSN) applications. WSNs are characterised by limited resources from a computational and energy perspective; in addition, the integrity of the WSN coverage area may be compromised over the duration of the network's operational lifetime, as environmental effects amongst others take their toll. Thus a significant problem arises--how can an agent construct an accurate model of the prevailing situation in order that it can make effective decisions about future courses of action within these constraints? In this paper, one popular agent architecture, the BDI architecture, is examined from this perspective. In particular, the fundamental issue of belief generation within WSN constraints using classical reasoning augmented with a fuzzy component in a hybrid fashion is explored in terms of energy-awareness and utility.