An intelligent agent for fault reconnaissance in sensor networks

An embedded sensor network is a system of nodes, each of which is equipped with a certain amount of sensing, actuating, computation, communication and storage components. Two major components of sensor nodes are sensing unit and wireless transceiver. They directly interact with nodes in wireless sensor networks (WSNs) that are easily prone to failure due to hardware failure, communication link errors, energy depletion, malicious attacks, etc. Even if the sensor node hardware is in excellent condition, still the communication between sensor nodes depends on many factors such as signal strength, obstacles and interference. Degradation in these factors results in low reliability of sensor nodes. One of the key prerequisite for an effective, efficient embedded sensor network is utilization of low-cost, low-overhead and high-resilient fault-inference techniques. Our attempt is to address fault-inference issues in sensor networks using an agent-based approach. Our proposed approach involves an intelligent agent that outfitted with a fault-inference engine. This engine profits from Expectation Maximization (EM) algorithm to evaluate fault probabilities of sensor nodes. Our experiment in a wireless sensor testbed is conducted to demonstrate the correctness and effectiveness of our approach.