Adaptive Monitor Placement for Near Real-time Node Failure Localisation in Wireless Sensor Networks

As sensor-based networks become more prevalent, scaling to unmanageable numbers or deployed in difficult reach areas, real-time failure localisation is becoming essential for continued operation. Network tomography, a system and application-independent approach, has been successful localising complex failures (i.e., observable by end-to-end global analysis) traditional networks. Applying network tomography wireless sensor (WSNs), however, challenging. First, WSN topology changes due environmental interactions (e.g., interference). Additionally, the selection of devices running monitoring processes (monitors) an NP-hard problem. Monitors observe in-network properties identify failures, with their placement impacting number identifiable failures. Since consumes in-node resources, it minimise while maintaining tomography’s effectiveness. Unfortunately, state-of-the-art solutions solve this optimisation problem using time-consuming greedy heuristics. In article, we propose two efficiently applying Tomography WSNs: graph compression scheme, enabling faster monitor reducing edges network, adaptive algorithm recovering given changes. The experiments show that our solution at least 1,000× than approaches copes variations large-scale WSNs.