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We present a suite of algorithms for self-organization of wireless sensor networks, in which there is a scalably large number of mainly static nodes with highly constrained energy resources. The protocols further support slow mobility by a subset of the nodes, energy-efficient routing, and formation of ad hoc subnetworks for carrying out cooperative signal processing functions among a set of the nodes.

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Abstract-A distributed power-control algorithm with active link protection (DPC/ALP) is studied in this paper. It maintains the quality of service of operational (active) links above given thresholds at all times (link quality protection). As network congestion builds up, established links sustain their quality, while incoming ones may be blocked and rejected. A suite of admission control algorithms, based on the DPC/ALP one, is also studied. They are distributed/autonomous and operate using local interference measurements.A primarily networking approach to power control is taken here, based on the concept of active link protection, which naturally supports the implementation of admission control. Extensive simulation experiments are used to explore the network dynamics and investigate basic operational effects/tradeoffs related to system performance.

This tutorial presents a detailed study of sensor faults that occur in deployed sensor networks and a systematic approach to model these faults. We begin by reviewing the fault detection literature for sensor networks. We draw from current literature, our own experience, and data collected from scientific deployments to develop a set of commonly used features useful in detecting and diagnosing sensor faults. We use this feature set to systematically define commonly observed faults, and provide examples of each of these faults from sensor data collected at recent deployments.

We propose an entropy-based sensor selection heuristic for localization. Given 1) a prior probability distribution of the target location, and 2) the locations and the sensing models of a set of candidate sensors for selection, the heuristic selects an informative sensor such that the fusion of the selected sensor observation with the prior target location distribution would yield on average the greatest or nearly the greatest reduction in the entropy of the target location distribution. The heuristic greedily selects one sensor in each step without retrieving any actual sensor observations. The heuristic is also computationally much simpler than the mutual-information-based approaches. The effectiveness of the heuristic is evaluated using localization simulations in which Gaussian sensing models are assumed for simplicity. The heuristic is more effective when the optimal candidate sensor is more informative.

Wireless sensor networks constitute the platform of a broad range of applications related to national security, surveillance, military, health care, and environmental monitoring. The coverage problem for Wireless Sensor Network (WSN) has been studied extensively in recent years, especially when combined with connectivity and energy efficiency. This paper focuses on the sensor replacement problem in wireless sensor networks consists of mobile sensors. Mobility equipped sensors are utilized to recover and maintain the overall coverage using the dynamic cluster concept. The proposed fault repair solution does not assume the localization information is available. Mobile sensor nodes make use of simple geometric operation to locate and replace dying nodes to recover or increase the existing coverage and connectivity.

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