Continuous data collection in wireless sensor networks

Recently, it has come to be generally believed by academia and industry alike that the sensor network will have a key role to extend the reachability of the next generation Internet. A key characteristic of this network is that there is no single node in the network that is powerful enough to perform the assigned tasks. An application should be served via the cooperation of several nodes or even the entire network. The network serves as an information base, and is data driven, as opposed to a provider for the point-to-point connection. The main challenge of this network is huge information organization, including information storage, searching and retrieval, especially in a continuous way. There are many specific and interrelated problems. We list a few examples. First, data accuracy: the correctness of the sensor network to represent the properties of the sensor field. Second, data search and retrieval delay; while low delay is always preferred, various applications have different delay constraints. Third, overhead; low transmission overhead is often the main consideration in system design, as it is directly related to the usage of energy, the most severely limited resource for sensors. In this thesis, we first discuss load balanced sensor coverage, which provides a lower layer support for long run sensor data collection. We then concentrate on how to balance the parameters in data collection of the sensor networks, so that the user queries and applications can be satisfied with reasonable delay and low overhead. Based on different application specifics, we try to use a smaller number of sensors, less number of transmissions by exploring historical and topological information, coding techniques and data distribution information. Our analysis and experimental results show that our architecture and algorithms provide both theoretical and practical insights for sensor network design and deployment.