ABAMA: An Agent-based Architecture for Mapping Natural Ecosystems onto Wireless Sensor Networks

Wireless Sensor Networks (WSNs) comprise of hundreds of spatially distributed sensors which may collaborate, compete, and self-organize in order to solve complex tasks which are beyond their individual capabilities. The efficiency of these actions is commonly restricted by the limited energy, the environmental context, and the processing capabilities of the sensors. To overcome these constraints, we explore the ecosystem metaphor for WSNs with the aim of taking advantage of the efficient adaptation behavior and strong communication mechanisms used by living organisms. While mapping these organisms onto sensors and ecosystems onto WSNs, we identify the similarities of both parties in terms of structure, active entities, topology, goals, communications, and functions and highlight shortcomings that would prevent WSNs from matching the behavior of ecosystems. We then propose an agent-based architecture that migrates the complex processing loads outside the physical sensor network while incorporating missing characteristics such as autonomy, intelligence, and context awareness to the WSN. In contrast to existing works, we use software agents to bridge the gap between WSNs and natural ecosystems and achieve an optimal mapping between both systems. Our ultimate goal is to enhance the capabilities of WSNs to take advantage of ecology-inspired algorithms.