Storage-centric Sensor Networks for Smart Buildings

In my thesis, I propose a model-based systems design framework, called WSNDesign, to facilitate the design and implementation of wireless sensor networks (WSNs). WSNDesign provides a hierarchy of model libraries to model various behaviors and structures of WSNs in the context of Smart Buildings, and introduces a system design flow to compose both continuous-time and event-triggered modules to develop applications with support for performance evaluation. In order to handle various sensor data efficiently, WSNDesign provides a distributed database system, called HybridDB, for data collection and retrieval. HybridDB enables sensors to store large-scale datasets in situ on local NAND ash using a novel resource-aware data storage system, and can process typical queries inWSNs extremely efficiently. In addition, HybridDB supports incremental -approximate querying that enables clients to retrieve a just-sufficient set of sensor data by issuing refinement and zoom-in sub-queries to search events and analyze sensor data efficiently. HybridDB can always return an approximate dataset with guaranteed L1-norm error bound.