Compressed topology tomography in sensor networks

Wireless sensor network (WSN) topology tomography is essential for routing improvement, topology control, anomaly detection and load balance. Previous studies on WSN topology tomography are restricted to static routing tree estimation, which is unrealistic in real-world WSNs due to wireless channel dynamics. We study general WSN routing topology tomography from indirect measurements observed at the sink, where routing structure is dynamic. We formulate the problem as a novel compressed sensing problem, and present our decoding algorithm. We provide rigorous complexity analyses of our algorithm. Thorough simulations validate the effectiveness of our approach and algorithm.