Wireless sensor networks play an important role in a wide variety of applications such as environment monitoring and battlefield surveillance. The basic function of a wireless sensor network is to monitor its deployed region and transport sensor data to certain designated nodes. Therefore, coverage, capacity, and connectivity are three most fundamental properties for the operation and performance of a wireless sensor network. A deep understanding of these properties and their interrelationship is of great importance for the network planning, algorithm design, and performance of wireless sensor networks.
This project aims to establish a strong theoretical foundation and design practical protocols to provide high performance coverage, capacity, and connectivity in wireless sensor networks. Wireless sensor networks have many unique characteristics differing from other wireless networks, including heterogeneous sensing, communication, and mobility capabilities of sensor nodes, limited infrastructure and power supply, and traffic pattern where data mainly flow from sensors to data sinks rather than between peer nodes. This research integrates the concepts and techniques in wireless communications, stochastic modeling, geometry, and combinatorial optimizations to construct analytical models and develop practical solutions.
The expected outcomes include: (i) fundamental limits of the coverage, capacity, and connectivity under various network scenarios; (ii) efficient algorithms for robust coverage, connectivity, and data transportation; (iii) a test-bed to validate the analytical results and evaluate the performance of algorithms via real experiments. This project also includes a strong educational component that promotes teaching, training, and learning through the active involvement of research students.
