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**11 - 20**of**20**### 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 real-life 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 real-life 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 multi-hop 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

### 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 multi-hop 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.

### 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.

### 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.

### RF-Based Localization in GPS-Denied 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 radio-based 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 Self-Organizing 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) Range-free schemes that use radio proximity information, as in the SOM approach; and 2) Range-based schemes that measure the attenuation of the Radio-Frequency (RF) signal to estimate

### Distributed Localization and Clustering Using Data Correlation and the Occam’s Razor Principle

"... Abstract—We present a distributed algorithm for computing a combined solution to three problems in sensor networks: localization, clustering, and sensor suspension. Assuming that initially only a rough approximation of the sensor positions is known, we show how one can use sensor measurements to ref ..."

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Abstract—We present a distributed algorithm for computing a combined solution to three problems in sensor networks: localization, clustering, and sensor suspension. Assuming that initially only a rough approximation of the sensor positions is known, we show how one can use sensor measurements to refine the set of possible sensor locations, to group the sensors into clusters with linearly correlated measurements, and to decide which sensors may suspend transmission without jeopardizing the consistency of the collected data. Our algorithm applies the “Occam’s razor principle ” by computing a “simplest ” explanation for the data gathered from the network. We also present centralized algorithms, as well as efficient heuristics. I.

### Journal of Computational Geometry jocg.org GOOD QUALITY VIRTUAL REALIZATION OF UNIT DISK GRAPHS ∗

"... Abstract. The quality of an embedding Φ: V 7 → R2 of a graph G = (V,E) into the Euclidean plane is the ratio of max{u,v}∈E ||Φ(u) − Φ(v)||2 to min{u,v}6∈E ||Φ(u) − Φ(v)||2. Given a graph G = (V,E), that is known to be a unit disk graph (UDG), we seek algorithms to compute an embedding Φ: V 7 → R2 ..."

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Abstract. The quality of an embedding Φ: V 7 → R2 of a graph G = (V,E) into the Euclidean plane is the ratio of max{u,v}∈E ||Φ(u) − Φ(v)||2 to min{u,v}6∈E ||Φ(u) − Φ(v)||2. Given a graph G = (V,E), that is known to be a unit disk graph (UDG), we seek algorithms to compute an embedding Φ: V 7 → R2 of best (smallest) quality. Note that G comes with no associated geometric information and in this setting, related problems such as recognizing if G is a UDG, are NP-hard. While any UDG has a 2-dimensional embedding with quality between 1/4 and 1, the adaptation of Vempala’s random projection approach [38] by Kuhn et al. [22] provides the best quality bound of O(log3.5 n · √log log n). This paper presents a simple, combinatorial algorithm for computing an O(log3 n)-quality 2-dimensional embedding of a given graph, that is known to be a UDG. If the embedding is allowed to reside in higher dimensional space, we obtain improved results: a quality-2 embedding in RO(1). Our key technical contribution is the construction of a “growth-restricted approximation ” of the given UDG. Construction of a growth-restricted approximation permits us to bypass the standard and costly technique of solving a linear program with exponentially many “spreading constraints. ” As a side effect of our con-struction, we get the first constant-factor approximation to the minimum clique partition problem for UDGs, given without a geometric representation. Our problem is a version of the well known localization problem in wireless sensor networks, in which network nodes are required to compute virtual 2-dimensional Euclidean coordinates given little or (as in our case) no geometric information. 1

### Research Article Fully Decentralized and Collaborative Multilateration Primitives for Uniquely Localizing WSNs

"... License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computa ..."

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License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. We provide primitives for uniquely localizing WSN nodes. The goal is to maximize the number of uniquely localized nodes assuming a fully decentralized model of computation. Each node constructs a cluster of its own and applies unique localization primitives on it. These primitives are based on constructing a special order for multilaterating the nodes within the cluster. The proposed primitives are fully collaborative and thus the number of iterations required to compute the localization is fewer than that of the conventional iterative multilateration approaches. This further limits the messaging requirements. With relatively small clusters and iteration counts, we can localize almost all the uniquely localizable nodes. 1.

### Good Quality Virtual Realization of Unit Disk Graphs

, 2009

"... The quality of an embedding Φ: V ↦ → R 2 of a graph G = (V, E) into the Euclidean plane is the ratio of max {u,v}∈E ||Φ(u) − Φ(v)||2 to min {u,v}∈E ||Φ(u) − Φ(v)||2. Given a graph G = (V, E), that is known to be a unit disk graph (UDG), we seek algorithms to compute an embedding Φ: V ↦ → R 2 of be ..."

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The quality of an embedding Φ: V ↦ → R 2 of a graph G = (V, E) into the Euclidean plane is the ratio of max {u,v}∈E ||Φ(u) − Φ(v)||2 to min {u,v}∈E ||Φ(u) − Φ(v)||2. Given a graph G = (V, E), that is known to be a unit disk graph (UDG), we seek algorithms to compute an embedding Φ: V ↦ → R 2 of best (smallest) quality. Note that G comes with no associated geometric information and in this setting, related problems such as recognizing if G is a UDG, are NP-hard. While any UDG that is not a clique has a 2-dimensional embedding with quality between 1/2 and 1, the adaptation of Vempala’s random projection approach (FOCS 1998) by Kuhn et al. (Algorithmica, to appear) provides the best quality bound of O(log 3.5 n · √ log log n). This paper presents a simple, combinatorial algorithm for computing a O(log 2.5 n)-quality 2-dimensional embedding of a given graph, that is known to be a UDG in the Euclidean plane. If the embedding is allowed to reside in higher dimensional space, we obtain improved results: a quality-2 embedding in R O(1). Our key technical contribution is the construction of a “growth-restricted approximation ” of the given UDG. While such a construction is trivial if the UDG comes with a geometric representation, we are not aware of any other algorithm that can perform this step without geometric information. Construction of a growth-restricted approximation permits us to bypass the standard and costly technique of solving a linear program with exponentially many “spreading constraints. ” As a side effect of our construction, we get the first constant-factor approximation to the minimum clique partition problem for UDGs, given without a geometric representation. Our problem is a version of the well known localization problem in wireless sensor networks, in which network nodes are required to compute virtual 2-dimensional Euclidean coordinates given little or (as in our case) no geometric information.

### Cooperative Localization In Wireless Networked Systems

, 2007

"... Cooperative localization in wireless networked systems ..."

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