| Summary: | Sensor networks comprise resource-constrained wireless nodes with the capability of gathering information about their surroundings and have recently risen to prominence with the promise of being an effective computing platform for diverse applications, ranging from event detection to environmental monitoring. The database community proposed the use of sensor network query processors (SNQPs) as means to meet data collection requirements using a declarative query language. Declarative queries posed against a sensor network constitute an effective means to repurpose sensor networks and reduce the high software development costs associated with them. The range of sensor network applications is very broad. Such applications have diverse, and often conflicting, QoS expectations in terms of the delivery time of results, the acquisition interval at which data is collected, the total energy consumption of the deployment, or the network lifetime. The conflicting nature of these desiderata is aggravated by the resource-constrained nature of sensor networks as a computing fabric, making it particularly challenging to reconcile the trade-offs that arise. Previously, SNQPs have been focussed on evaluating queries as energy-efficiently as possible. There has been comparatively less work on attempting to meet a broad range of optimization goals and constraints that captured these QoS expectations. In this respect, previous work in SNQP has not aimed at being general purpose across the breadth of applications to which sensor networks have been applied. This PhD dissertation presents an approach for enabling QoS-awareness in SNQPs so that query evaluation plans are generated that exhibit good performance for a broader range of sensor network applications in terms of their QoS expectations. The research contributions reported here include (a) a functional decomposition of the decision-making steps required to compile a declarative query into a query evaluation plan in a sensor network setting; (b) algorithms to implement these decision-making steps; and (c) an empirical evaluation to show the benefits of QoS-awareness compared to a representative fixed-goal SNQP.
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