In a domain with diverse multi-disciplinary views of what a Wireless Sensor Network (WSN) is, tracking progress and developing efficient WSNs is inherently a complex process. The main motivation of this work is advancing state-of-the-art WSNs by adaptively utilizing their components, and enlisting the utility of resources in network vicinity. As WSNs increase in density and expand in scale, we continue to witness an increase in overlapped deployments that serve independent applications. In most scenarios, new networks are deployed for new applications without considering previous or neighboring WSNs. This thesis presents the resource reuse (RR-WSN) paradigm. Adopting a generic framework for resource utilization, we achieve synergy between heterogeneous sensing systems. We abstract the view of a WSN in terms of functional capabilities, and offer a component-based view to boost sensor node (SN) potential and contribution to WSN operation. Thus SNs provide resources. On the other hand, we formally derive a set of functional requirements per application. The design and deployment of WSNs thus converges to an optimal assignment of functional requirements to resources. Two mainstream designs of WSNs are addressed in this thesis. The first involves WSNs with static deployments of nodes, whereby multiple applications run on networks in a given vicinity, yet the resources and applications share an owner (e.g., on a University Campus). We then present a Binary Integer Programming formulation to find the optimal assignment of resources to these functional requirements, while minimizing the energy impact of running each functional request. We further extend our scope to include WSNs that depend on transient nodes, such as smartphones, in a dynamic (DRR-WSN) paradigm, which could contribute significantly to the resource pool. Intuitively, multiple-owners are involved as resource providers and require different applications. Thus, we address the valuation of resources as they are shared across network owners. We finally present a maximal matching problem of finding the lowest cost for running each application, based on the available resource pool in the vicinity required. Extensive performance evaluation depicts the impact of RR-WSN design on WSN operation and longevity in various scenarios. / Thesis (Ph.D, Computing) -- Queen's University, 2013-08-27 04:44:14.556