Resource provisioning and management in hybrid sensor networks

The development of embedded system technologies have made it feasible to deploy large-scale sensor and actuator networks. These networks are revolutionizing the way in which we understand, monitor and control complex physical environment, and provide one of the missing connections between the Internet and the physical world. Because of size, form factor and cost considerations, wireless sensor networks suffer from severe resourceconstraints, such as communication bandwidth and range, computation power, memory and energy. Furthermore, sensor networks are expected to consist of hundreds of sensors in the future. The resource constraints of tiny embedded devices, together with the large network size, create many research challengeswhich do not appear in traditional networks. In this dissertation, we address the challenges involved in designing robust and scalable sensor network system. In contrast to the flat networking model considered in previous sensor networks research, we propose a hierarchical or hybrid network architecture which is more scalable and robust. Hybrid sensor networks consist of resource-impoverished sensors and resource-rich sensors, called micro-servers. Because of the different capabilities of heterogeneous devices in hybrid sensor networks, there is need for effective deployment and utilization of network resources. Therefore, we introduce resource provisioning and management algorithms to optimize the performance of hybrid sensor networks. The first contribution of this dissertation is the design and implementation of new network architecture and algorithms to address the computation power and memory limitations of tiny embedded devices. The second contribution of this dissertation is the design and evaluation of an Anycast communication paradigm for hybrid sensor and actuator networks. We propose and evaluate a reverse tree-based Anycast mechanism tailored to deal with the unique event dynamics in sensor networks. The third contribution of this dissertation is the design and evaluation of an energy provisioning and management algorithm for hybrid sensor and actuator networks. Our studies show that the location of extra energy-provisioning can affect the lifetime ofsystem dramatically; and hybrid sensor networks are financially cost-effective for a large number of cases which makes them a scalable solution. Together, these contributions enable effective resource provisioning and management in hybrid sensor networks