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Sensor nodes in Wireless Sensor Networks (WSNs) are prone to failures due to the fragile hardware, malicious attacks, or hostile or harsh environment. In order to assure reliable, long-term monitoring of the phenomenon under investigation, a major challenge is to detect node malfunctions as soon as possible and with an energy efficient approach. We address this problem by using a system-level diagnosis strategy in which the sink issues to the WSN a self-diagnosis task that involves a number of mutual tests among sensors. Based on the test outcomes, the sink executes the diagnosis procedure. This work presents an algorithm for the assignment of tests among the sensors of a WSN that assures the desired system diagnosability and that is aware of energy consumption. We show by simulation experiments that the present approach, as compared to a previous one, enables consistent energy savings on the sensors.

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The Distributed Network Connectivity algorithm allows every node in a general topology network to determine which portions of the network are reachable and unreachable. The algorithm consists of three phases: test, dissemination, and connectivity computation. During the testing phase each link is tested by one of the adjacent nodes at alternating testing intervals. Upon the detection of a new unresponsive link, the tester starts the dissemination phase, in which a distributed breadth-first tree is employed to inform the other connected nodes about the event. At any time, any working node may run the third phase, in which a graph connectivity algorithm shows the network connectivity. We prove bounds on the worst case latency of the algorithm. Simulation results of the dissemination of one event are presented for a number of network topologies, and compared to other algorithms.