Wireless Sensor Networks have been proposed for a multitude of location-dependent applications. For such systems, the cost and limitations of hardware on sensing nodes prevent the use of range-based localization schemes that depend on absolute point-to-point distance estimates. Because coarse accuracy is sufficient for most sensor network applications, solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches. In this paper, we present APIT, a novel localization algorithm that is range-free. We show that our APIT scheme performs best when an irregular radio pattern and random node placement are considered, and low communication overhead is desired. We compare our work via extensive simulation, with three state-of-the-art range-free localization schemes to identify the preferable system configurations of each. In addition, we study the effect of location error on routing and tracking performance. We show that routing performance and tracking accuracy are not significantly affected by localization error when the error is less than 0.4 times the communication radio radius. 1.

Many sensor network applications require location awareness, but it is often too expensive to include a GPS receiver in a sensor network node. Hence, localization schemes for sensor networks typically use a small number of seed nodes that know their location and protocols whereby other nodes estimate their location from the messages they receive. Several such localization techniques have been proposed, but none of them consider mobile nodes and seeds. Although mobility would appear to make localization more difficult, in this paper we introduce the sequential Monte Carlo Localization method and argue that it can exploit mobility to improve the accuracy and precision of localization. Our approach does not require additional hardware on the nodes and works even when the movement of seeds and nodes is uncontrollable. We analyze the properties of our technique and report experimental results from simulations. Our scheme outperforms the best known static localization schemes under a wide range of conditions.

Pervasive networks of micro-sensors and actuators offer to revolutionize the ways in which we understand and construct complex physical systems. Sensor networks must be scalable, long-lived and robust systems, overcoming energy limitations and a lack of pre-installed infrastructure. We explore three themes in the design of self-configuring sensor networks: tuning density to trade operational quality against lifetime; using multiple sensor modalities to obtain robust measurements; and exploiting fixed environmental characteristics. We illustrate these themes through the problem of localization, which is a key building block for sensor systems that itself requires coordination.

In wireless sensor networks (WSNs), sensors ’ locations play a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery (localization) schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the reference information provided by these beacon nodes. Most of the beacon-based localization schemes assume a benign environment, where all beacon nodes are supposed to provide correct reference information. However, when the sensor networks are deployed in a hostile environment, where beacon nodes can be compromised, such an assumption does not hold anymore. In this paper, we propose a general scheme to detect localization anomalies that are caused by adversaries. Our scheme is independent from the localization schemes. We formulate the problem as an anomaly intrusion detection problem, and we propose a number of ways to detect localization anomalies. We have conducted simulations to evaluate the performance of our scheme, including the false positive rates, the detection rates, and the resilience to node compromises. 1.

Abstract — In wireless sensor networks (WSNs), sensor location plays a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the information provided by these beacon nodes. In this paper, we show that efficient location discovery can be achieved in sensor networks without using beacons. We propose a beacon-less location discovery scheme. based on the following observations: in practice, it is quite common that sensors are deployed in groups, i.e., sensors are put into n groups, and sensors in the same group are deployed together at the same deployment point (the deployment point is different from the sensors ’ final resident location). Sensors from the same group can land in different locations, and those locations usually follow a probability distribution that can be known a priori. With this prior deployment knowledge, we show that sensors can discover their locations by observing the group memberships of its neighbors. We model the location discovery problem as a statistical estimation problem, and we use the Maximum Likelihood Estimation method to estimate the location. We have conducted experiments to evaluate our scheme. Keyword: System Design. I.

Abstract — In this paper we present a novel sequence-based RF localization algorithm called Ecolocation. Our algorithm determines the location of unknown nodes by examining the ordered sequence of received signal strength (RSS) measurements taken at multiple reference nodes. We employ a constraint-based approach that provides for robust location decoding even in the presence of random RSS fluctuations due to multipath fading and shadowing. Through extensive systematic simulations, and a representative set of real mote experiments, we show that over a wide range of settings Ecolocation performs better than other state of the art approaches in terms of localization accuracy and precision. I.

OF THE DISSERTATION University of California, Los Angeles, 2002 Professor Deborah L. Estrin, Chair Recent technological advances have fostered the emergence of small, low-power devices that integrate micro-sensing and actuation with on-board processing and wireless communications capabilities. Through distributed coordination, pervasive networks of micro-sensors and actuators are expected to revolutionize the ways in which we understand and construct complex physical systems. Fundamental to such coordination is localization, or the ability to establish spatial relationships among objects.

Recent advancement in radio and processor technology has seen the rise of Wireless Sensor Networks (WSN) as a reliable and cost-effective tool for real-time information gathering and analysis tasks during emergency scenarios like natural disasters, terrorist attacks, military conflicts, etc. Post-deployment localization is extremely important and necessary in these applications. But, current distributed localization approaches are not designed for such highly hostile and dynamic network conditions. This dissertation studies the adverse effects of factors like cheating behavior, node disablement and measurement inconsistencies on the corresponding localization protocols and attempts to provide simple and efficient solutions in order to overcome these problems. The first problem addressed in this dissertation is, how to perform efficient distance-based localization in the presence of cheating beacon nodes? This dissertation attempts to answer two fundamental questions in distance-based localization: (i) In the presence of cheating beacons, what are the necessary and sufficient conditions to guarantee a bounded localization error? and (ii) Under these conditions, what class of algorithms can provide that error bound? In this part of the dissertation, it is shown that when the number of cheating beacons is greater than or equal to some

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