Wireless Sensor Networks in Motion - Clustering Algorithms for Service Discovery and Provisioning

The evolution of computer technology follows a trajectory of miniaturization and diversification. The technology has developed from mainframes (large computers used by many people) to personal computers (one computer per person) and recently, embedded computers (many computers per person). One of the smallest embedded computers is a wireless sensor node, which is a batterypowered miniaturized device equipped with processing capabilities, memory, wireless communication and sensors that can sense the physical parameters of the environment. A collection of sensor nodes that communicate through the wireless interface form a Wireless Sensor Network (WSN), which is an ad-hoc, self organizing network that can function unattended for long periods of time. Although traditionally WSNs have been regarded as static sensor arrays used mainly for environmental monitoring, recently, WSN applications have undergone a paradigm shift from static to more dynamic environments, where nodes are attached to moving objects, people or animals. Applications that use WSNs in motion are broad, ranging from transport and logistics to animal monitoring, health care and military, just to mention a few. These application domains have a number of characteristics that challenge the algorithmic design of WSNs. Firstly, mobility has a negative effect on the quality of the wireless communication and the performance of networking protocols. Nevertheless, it has been shown that mobility can enhance the functionality of the network by exploiting the movement patterns of mobile objects. Secondly, the heterogeneity of devices in a WSN has to be taken into account for increasing the network performance and lifetime. Thirdly, the WSN services should ideally assist the user in an unobtrusive and transparent way. Fourthly, energy-efficiency and scalability are of primary importance to prevent the network performance degradation. This thesis focuses on the problems and enhancements brought in by networ mobility, while also accounting for heterogeneity, transparency, energy efficiency and scalability. We propose a set of algorithms that enable WSNs to self-organize efficiently in the presence of mobility, adapt to and even exploit dynamics to increase the functionality of the network. Our contributions include an algorithm for motion detection, a set of clustering algorithms that can be used to handle mobility efficiently, and a service discovery protocol that enables dynamic user access to the WSN functionality.