Cognitive sensing for body sensor networks

Cognitive sensor networks are based on the deployment of a large number of sensors for intelligently and autonomically acquiring localised and situated information of the sensing environment. Due to the inherent complexities involved in managing a large number of wireless sensors, bio-inspired sensing and networking has attracted significant research interest in recent years. The use of bio-inspired sensing generally involves the specification of a set of simple rules and how they should be iteratively applied to the population. One well known example of such an approach is swarm intelligence developed in artificial intelligence for studying the collective behaviour of decentralised, self-organised systems. Another example of bio-inspired sensing and networking is quorum sensing. Quorum sensing is the ability of bacteria to communicate and coordinate behaviour via signalling molecules. Quorum sensing is a useful concept for sensor networks because the bacterial cells need to be aware of the global cell concentration, and in the same way a sensor needs to know if there are enough sensors to form a cluster for the purpose of monitoring a particular area of the network collectively. These examples show how simple mechanisms can lead to an effective collective behaviour with functionality and adaptivity amplified on a global scale in the absence of a rigid central management structure. The biological connotation of cognitive and autonomic sensing is not coincidental. It reflects our inspiration by biological systems, which are able to manage complex networks so effectively and gracefully. The purpose of this presentation is to outline some of the key features and research challenges in cognitive sensing and demonstrate the use of this alternate paradigm based on the strategies used by biological systems to deal with the challenges of scale, complexity, heterogeneity, and uncertainty involved in pervasive sensing.