Programming Wireless Sensor Networks: From Static to Adaptive Models

Wireless Sensor Networks (WSNs) are a rapidly emerging research area because of their vast application vistas in real-world environments, as well as their rapid deployments at low cost and with high flexibility. In 2003, Technology Review ranked WSNs among 10 emerging technologies that will change the world. WSNs consist of tiny sensor nodes that can be easily embedded in the environment, establish a wireless ad-hoc network, and compose a distributed system to collaboratively sense physical phenomena and process sensed data, or to react to the environment based on the sensed data. To practically use this technology, WSNs must be able to operate unattended for long periods of time, especially when deployed in inaccessible places. Moreover, their new applications in heterogeneous and ubiquitous settings make the autonomy of their operations very important. This introduces several new requirements, such as reconfiguration of WSNs to meet future unpredictable needs, remote maintenance of sensor software, adapting WSN functionality against changes in heterogeneous environments, and remote patching of sensor software to handle after-deployment faults. To address these requirements, we need to study the fundamental issue of reprogramming and software reconfiguration in WSNs and devise a framework that provides the primitives required to enable dynamicity in sensor software. This thesis focuses on this issue and presents a set of WSN programming frameworks that simplify application development in a range of settings, from static deployments with pre-defined and constant conditions to dynamic deployments with changing and unpredictable requirements. In particular, the contributions of this thesis are mainly within the following four areas. The first part presents a distributed middleware system, called WiSeKit, to enable adaptation and reconfiguration of WSN applications in ubiquitous and context-aware environments. WiSeKit proposes a middleware software framework that formulates the process of adaptive WSN application development and abstracts the underlying technological adaptation processes. The adaptation strategy is inspired by the main activities of the feedback control loop, including context-awareness, adaptation reasoning, and software reconfiguration. In particular, it introduces a novel context processing model to monitor various context information (e.g., sensor resources and environmental changes) in WSNs. The analyzed context data is delivered to a hierarchical adaptation reasoning framework to make decisions about what adaptation to perform. Finally, WiSeKit pro-