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20
SpiderBat: Augmenting Wireless Sensor Networks with Distance and Angle Information
, 2011
"... Having access to accurate position information is a key requirement for many wireless sensor network applications. We present the design, implementation and evaluation of SpiderBat, an ultrasoundbased ranging platform designed to augment existing sensor nodes with distance and angle information. Sp ..."
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Having access to accurate position information is a key requirement for many wireless sensor network applications. We present the design, implementation and evaluation of SpiderBat, an ultrasoundbased ranging platform designed to augment existing sensor nodes with distance and angle information. SpiderBat features independently controllable ultrasound transmitters and receivers, in all directions of the compass. Using a digital compass, nodes can learn about their orientation, and combine this information with distance and angle measurements using ultrasound. To the best of our knowledge, SpiderBat is the first ultrasoundbased sensor node platform that can measure absolute angles between sensor nodes accurately. The availability of angle information enables us to estimate node positions with a precision in the order of a few centimeters. Moreover, our system allows to position nodes in multihop networks where pure distancebased algorithms must fail, in particular in sparse networks, with only a single anchor node. Furthermore, information on absolute node orientations makes it possible to detect whether two nodes are in lineofsight. Consequently, we can detect the presence of obstacles and walls by looking at patterns in the received ultrasound signal.
Universal Rigidity and Edge Sparsification for Sensor Network Localization
, 2009
"... Owing to their high accuracy and ease of formulation, there has been great interest in applying convex optimization techniques, particularly that of semidefinite programming (SDP) relaxation, to tackle the sensor network localization problem in recent years. However, a drawback of such techniques is ..."
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Owing to their high accuracy and ease of formulation, there has been great interest in applying convex optimization techniques, particularly that of semidefinite programming (SDP) relaxation, to tackle the sensor network localization problem in recent years. However, a drawback of such techniques is that the resulting convex program is often expensive to solve. In order to speed up computation, various edge sparsification heuristics have been proposed, whose aim is to reduce the number of edges in the input graph. Although these heuristics do reduce the size of the convex program and hence making it faster to solve, they are often ad hoc in nature and do not preserve the localization properties of the input. As such, one often has to face a tradeoff between solution accuracy and computational effort. In this paper we propose a novel edge sparsification heuristic that can provably preserve the localization properties of the original input. At the heart of our heuristic is a graph decomposition procedure, which allows us to identify certain sparse generically universally rigid subgraphs of the input graph. Our computational results show that the proposed approach can significantly reduce the computational and memory complexities of SDP–based algorithms for solving the sensor network localization problem. Moreover, it compares favorably with existing speedup approaches, both in terms of accuracy and solution time. 1
Multiscale Anchorfree Distributed Positioning in Sensor Networks
"... Abstract—Positioning is one of the most fundamental problems in sensor networks: Given the network’s connectivity graph and some additional local information on measured distances and/or angles, the goal is to recover the nodes ’ positions. Varying the assumptions regarding the nature and the qualit ..."
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Abstract—Positioning is one of the most fundamental problems in sensor networks: Given the network’s connectivity graph and some additional local information on measured distances and/or angles, the goal is to recover the nodes ’ positions. Varying the assumptions regarding the nature and the quality of the measurements, there has been extensive research for both hardness results and practical, distributed, positioning schemes. This paper addresses these issues for a setting that appears to be most likely in realworld scenarios in the future – nodes can roughly measure distances and relative angles. We will show that this problem is N Phard like most positioning problems even for arbitrarily small errors. We will also propose an algorithm combining robustness to erroneous measurements and scalability in a completely distributed fashion and provide simulation results for networks of up to 128k nodes with varying errors. I.
Collaborative Location Certification for Sensor Networks
"... Location information is of essential importance in sensor networks deployed for generating locationspecific event reports. When such networks operate in hostile environments, it becomes imperative to guarantee the correctness of event location claims. In this paper we address the problem of assessi ..."
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Location information is of essential importance in sensor networks deployed for generating locationspecific event reports. When such networks operate in hostile environments, it becomes imperative to guarantee the correctness of event location claims. In this paper we address the problem of assessing location claims of untrusted (potentially compromised) nodes. The mechanisms introduced here prevent a compromised node from generating illicit event reports for locations other than its own. This is important because by compromising “easy target” sensors (say, sensors on the perimeter of the field that’s easier to access), the adversary should not be able to impact data flows associated with other (“premium target”) regions of the network. To achieve this goal, in a process we call location certification, data routed through the network is “tagged ” by participating nodes with “belief ” ratings, collaboratively assessing the probability that the claimed source location is indeed correct. The effectiveness of our solution relies on the joint knowledge of participating nodes to assess the truthfulness of claimed locations. By collaboratively generating and propagating a set of “belief ” ratings with transmitted data and event reports, the network allows authorized parties (e.g. final data sinks) to evaluate a metric of trust for the claimed location of such reports. Belief ratings are derived from a data model of
Multiple round random ball placement: Power of second chance
 in COCOON ’09, 2009
"... In a pioneering work, Gupta and Kumar [8] studied the critical transmission range needed for the connectivity of random wireless networks. Their result implies that, given a square region of n×√ n, the asymptotic number of random nodes (each with transmission range 1) needed to form a connected net ..."
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In a pioneering work, Gupta and Kumar [8] studied the critical transmission range needed for the connectivity of random wireless networks. Their result implies that, given a square region of n×√ n, the asymptotic number of random nodes (each with transmission range 1) needed to form a connected network is Θ(n lnn) with high probability. This result has been used as cornerstones in deriving a number of asymptotic bounds for random multihop wireless networks, such as network capacity [7, 10, 11, 14]. In this paper we show that the asymptotic number of nodes needed for connectivity can be significantly reduced to Θ(n ln lnn) if we are given a “second chance ” to deploy nodes. More generally, under some deployment assumption, if we can deploy nodes in k rounds (for a constant k) and the deployment of the ith round can utilize the information gathered from the previous i − 1 rounds, we show that the number of nodes needed to provide a connected network with high probability isΘ(n ln(k) n). (See Eq (1) for the definition of ln(k) n.) Similar results hold when we need deploy sensors such that the sensing regions of all sensors cover the region of interest.
RFBased Localization in GPSDenied Applications
, 2009
"... Recent years have witnessed the emergence of novel application paradigms such as the Wireless Sensor Network and Context Aware computing. Among the challenges posed by these applications, localization – i.e. the process of locating people and/or devices – has emerged as a key problem that has found ..."
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Recent years have witnessed the emergence of novel application paradigms such as the Wireless Sensor Network and Context Aware computing. Among the challenges posed by these applications, localization – i.e. the process of locating people and/or devices – has emerged as a key problem that has found only partial answers. Although GPS receivers are common on many consumer electronic devices, alternative solutions are needed when locating devices that strive to be small and inexpensive, as in sensor networks, or when supporting indoor positioning. This dissertation focuses on radiobased positioning schemes suitable for applications where GPS is not a viable solution. The first part of this work addresses schemes that use proximity constraints inferred from radio connectivity. A novel solution based on the SelfOrganizing Map (SOM) formalism is proposed. Using extensive simulations, the SOM approach is shown to achieve a low localization error using limited computational resources. Comparison with other schemes demonstrate favorable results, especially in sparse deployments and when few (or none) of the nodes are located at known positions. The second part focuses on theoretical analysis of the results. Two broad families of positioning schemes are analyzed: 1) Rangefree schemes that use radio proximity information, as in the SOM approach; and 2) Rangebased schemes that measure the attenuation of the RadioFrequency (RF) signal to estimate
Random Deployment of Wireless Sensor Networks: Power of Second Chance
"... In a pioneering work, Gupta and Kumar [9] studied the critical transmission range needed for the connectivity of random wireless networks. Their result implies that, given a square region of √ n × n, the asymptotic number of random nodes (each with transmission range 1) needed to form a connected ne ..."
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In a pioneering work, Gupta and Kumar [9] studied the critical transmission range needed for the connectivity of random wireless networks. Their result implies that, given a square region of √ n × n, the asymptotic number of random nodes (each with transmission range 1) needed to form a connected network is Θ(n ln n) with high probability. This result has been used as cornerstones in deriving a number of asymptotic bounds for random multihop wireless networks, such as network capacity [8, 11, 12, 15]. In this paper we show that the asymptotic number of nodes needed for connectivity can be significantly reduced to Θ(n ln ln n) if we are given a “second chance ” to deploy nodes. More generally, under some deployment assumption, if we can randomly deploy nodes in k rounds (for a constant k) and the random deployment of the ith round can utilize the information gathered from the previous i − 1 rounds, we show that the number of nodes needed to provide a connected network with high probability is Θ(n ln (k) n). (See Eq (1) for the definition of ln (k) n.) Similar results hold when we need deploy sensors such that the sensing regions of all sensors cover the region of interest. Keywords Random deployment, wireless ad hoc networks, second chance, critical node number, critical transmission range. 1.
A Holistic Routing Protocol Design in Underground Wireless Sensor Networks
"... The traditional networking builds on layered protocol architecture to isolate the complexities in different layers. It has been realized that reallife wireless sensor networks (WSNs) must be considered holistically across different layers for optimum performance. We consider a special case of WSNs ..."
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The traditional networking builds on layered protocol architecture to isolate the complexities in different layers. It has been realized that reallife wireless sensor networks (WSNs) must be considered holistically across different layers for optimum performance. We consider a special case of WSNs that is deployed in underground tunnels. Underground communications present unique signal propagation characteristics due to the geographic and geological features, which in turn impact the underground network deployment and multihop routing patterns. We propose an efficient routing algorithm, called BRIT (Bounce Routing in Tunnels), for underground WSNs, and evaluate BRIT against the bottomline AODV in terms of network throughput, packet loss rate, stability and latencies using simulations. The contributions of the paper include a hybrid signal propagation model in three dimentional underground tunnels, an assortment of sensor deployment strategies in tunnels, an integrated routing metric (forwarding speed), and a route suppression mechanism. 1
1 DAL: A Distributed Localization in Sensor Networks Using Local Angle Measurement
"... Abstract—We study the localization problem in sensor networks by using local angle measurement. Localization using local angle information was recently proposed as an effective localization technique, which can be used for geographical routing with guaranteed delivery. However, the existing approach ..."
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Abstract—We study the localization problem in sensor networks by using local angle measurement. Localization using local angle information was recently proposed as an effective localization technique, which can be used for geographical routing with guaranteed delivery. However, the existing approach is based on linear programming (LP) and can not be implemented distributedly. We propose, design, and evaluate DAL: a purely distributed localization protocol in sensor networks using local angle measurement. Localization with local angle poses unique challenge in sensor networks due to information uncertainties identified in this paper. DAL specifically addresses these challenges. Via extensive simulations using ns2 and our own simulator, we show that the performance of DAL is comparable with that of the centralized LP approach in most cases. Our preliminary results with noisy angle measurement show that DAL keeps the global geometry of the sensor network fairly well. I.
1 A Device For Measuring Radio Frequency Angle of Arrival
"... Abstract—Much theory has been devised for node localization of wireless sensor networks (WSN). Localization based on angle measurements is more robust than localization based on distance measurements. Most research assumes the existence of a device with angle or distance measuring capabilities. This ..."
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Abstract—Much theory has been devised for node localization of wireless sensor networks (WSN). Localization based on angle measurements is more robust than localization based on distance measurements. Most research assumes the existence of a device with angle or distance measuring capabilities. This paper describes a small, low cost, proof of concept angle of arrival (AoA) measuring node. The premise involves rotating a directional reflector antenna assembly while measuring received signal strength (RSS). This procedure is defined under the assumption that RSS will be greatest when the reflector is pointed towards the transmitter source. The described node is shown to be a viable low cost option for measuring AoA to be used in a WSN.