Design And Implementation Of A Robust Monitor Assignment Algorithm For Sensor Network Tomography

With the development of the network technology, wireless sensor networks (WSNs) have been widely applied in more and more scenarios, such as military surveillance, medical, environmental protection, transportation monitoring, etc. The scale of WSNs deployment has increased from dozens of nodes to hundreds, even thousands of nodes. How to measurement such large scale sensor networks internal state efficiently and accurately is more and more important for analyzing and managing the WSNs. In wired networks, monitor-based network tomography has been proved to be an effective technology for network internal state measurements. However, those existing techniques cannot be applied into WSNs directly due to wireless dynamics. In this thesis, we study the problem to assign a number of sensor nodes as monitors in large scale sensor networks, so that the end-to-end measurements among monitors can be used to identify hop-by-hop link metrics. The contribution of this thesis is divided into the following two points:1. We proposes a confidence-based robust topology generation algorithm. Considering the dynamic of the WSNs, we merge a set of instant topologies into a robust one, which captures the dynamic changing topology over time.2. We proposes a cost-minimized monitor assignment algorithm. Using this robust topology, the cost-minimized monitor assignment algorithm assigns monitors with minimum overall cost. Comparing with other approaches, our approach assigns fewer monitors with high link metric identifiability and achieves a much smaller overall cost.We implement RoMA:a robust monitor assignment approach for WSNs measurement and evaluate its performance based on a deployed large scale sensor network:CitySee. Results show that RoMA achieves high identifiability with dynamically changing topology and is able to assign monitors with a much smaller overall cost.