Wireless Sensor Networks (WSNs) can experience problems (anomalies) during deployment, due to dynamic environmental factors or node hardware and software failures. These anomalies demand reliable detection strategies for supporting long term and/or large scale WSN deployments. Several strategies have been proposed for detecting specific WSN anomaly, yet there is still a need for more comprehensive anomaly detection strategies that jointly address network and node level anomalies. Intellectus methodology [23], [24], [25] build a tool that detected a new limited set of faults: sensor nodes may dynamically fail, be isolate and reboot and local topology control. These bugs are difficult to diagnose because the only externally visible characteristic is that no data is seen at the sink, from one or more nodes. This paper evaluate Intellectus methodology by different experiment in a Testbed network. In fact, Intellectus is be able to detect the injected fault and assess different scenarios of topology change.
