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Article Anchor Node Localization for Wireless Sensor Networks Using Video and Compass Information Fusion
, 2014
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SINUS: A Scalable and Distributed Routing Algorithm with Guaranteed Delivery for WSNs on High Genus 3D Surfaces
"... Abstract—In this paper, we put forward a novel scalable and distributed routing algorithm, called SINUS, for sensor networks deployed on the surface of complexconnected 3D settings such as tunnels, whose topologies are often theoretically modeled as high genus 3D surfaces. SINUS is carried out by f ..."
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Abstract—In this paper, we put forward a novel scalable and distributed routing algorithm, called SINUS, for sensor networks deployed on the surface of complexconnected 3D settings such as tunnels, whose topologies are often theoretically modeled as high genus 3D surfaces. SINUS is carried out by first slicing the genusn surface along a maximum cut set based on Morse theory and Reeb graph, in order to form a genus0 surface with 2n boundaries. Then, it groups these 2n boundaries into two groups each of which is next connected together. By doing so, a genus0 surface with exactly two boundaries emerges, which can be flattened into a strip, using the Ricci flow algorithm and next mapped to a planar annulus by Möbius Transform. By assigning nodes virtual coordinates on the planar annulus, SINUS finally realizes a variation of greedy routing to enable individual nodes to make local routing decisions. Our simulation results show that SINUS can achieve lowstretch routing with guaranteed delivery, as well as balanced traffic load. I.
A Distributed Delaunay Triangulation Algorithm Based on Centroidal Voronoi Tessellation for Wireless Sensor Networks
"... A wireless sensor network can be represented by a graph. While the network graph is extremely useful, it often exhibits undesired irregularity. Therefore, special treatment of the graph is required by a variety of network algorithms and protocols. In particular, many geometryoriented algorithms dep ..."
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A wireless sensor network can be represented by a graph. While the network graph is extremely useful, it often exhibits undesired irregularity. Therefore, special treatment of the graph is required by a variety of network algorithms and protocols. In particular, many geometryoriented algorithms depend on a type of subgraph called Delaunay triangulation. However, when location information is unavailable, it is nontrivial to achieve Delaunay triangulation by using connectivity information only. The only connectivitybased algorithm available for Delaunay triangulation is built upon the property that the dual graph for a Voronoi diagram is a Delaunay triangulation. This approach, however, often fails in practical wireless sensor networks because the boundaries of Voronoi cells can be arbitrarily short in discrete sensor network settings. In a sensor network with connectivity information only, it is fundamentally
Bubble Routing: A Scalable Algorithm with Guaranteed Delivery in 3D Sensor Networks
"... Abstract—Compared with its 2D counterpart, the scalability problem is greatly exacerbated in a 3D wireless sensor network. In this paper, we propose a scalable routing algorithm, dubbed Bubble Routing. It preprocesses global knowledge via a distributed algorithm, such that a node only needs to stor ..."
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Abstract—Compared with its 2D counterpart, the scalability problem is greatly exacerbated in a 3D wireless sensor network. In this paper, we propose a scalable routing algorithm, dubbed Bubble Routing. It preprocesses global knowledge via a distributed algorithm, such that a node only needs to store a small constant information to make correct and efficient local routing decisions and achieve guaranteed delivery at the same time. More specifically, the proposed bubble routing algorithm first decompose a 3D network into a set of hollow spherical cells (HSCs). A continuous and onetoone mapping is applied and a virtual tree structure is established inside each HSC to enable greedy routing. On the other hand, routing across HSCs is guided by a small routing table whose size is bounded by the number of interior holes. Our simulation results show that bubble routing can achieve guaranteed data delivery, low stretch factor, and well balanced traffic load. I.
2013 Proceedings IEEE INFOCOM Cut Graph Based Information Storage and Retrieval in 3D Sensor Networks with General Topology
"... Abstract—We address the problem of innetwork information processing, storage, and retrieval in threedimensional (3D) sensor networks in this research. We propose a geographic location free doublerulingbased scheme for largescale 3D sensor networks. The proposed approach does not require a 3D se ..."
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Abstract—We address the problem of innetwork information processing, storage, and retrieval in threedimensional (3D) sensor networks in this research. We propose a geographic location free doublerulingbased scheme for largescale 3D sensor networks. The proposed approach does not require a 3D sensor network with a regular cube shape or uniform node distribution. Without the knowledge of the geographic location and the distance bound, a data query simply travels along a simple curve with the guaranteed success to retrieve aggregated data through time and space with one or different types across the network. Simulations and comparisons show the proposed approach with low cost and a balanced traffic load. I.
SURF: A Connectivitybased Space Filling Curve Construction Algorithm in High Genus 3D Surface WSNs
"... Abstract—Many applications in wireless sensor networks (WSNs) require that sensor observations in a given monitoring area be aggregated in a serial fashion. This demands a routing path to be constructed traversing all sensors in that area, which is also called to linearize the network. In this paper ..."
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Abstract—Many applications in wireless sensor networks (WSNs) require that sensor observations in a given monitoring area be aggregated in a serial fashion. This demands a routing path to be constructed traversing all sensors in that area, which is also called to linearize the network. In this paper, we present SURF, a Space filling cURve construction scheme for high genus 3D surFace WSNs, yielding a traversal path provably aperiodic (that is, any node is covered at most a constant number of times). SURF first utilizes the hopcount distance function to construct the isocontour in discrete settings, then it uses the concept of the Reeb graph and the maximum cut set to divide the network into different regions. Finally it conducts a novel serial traversal scheme, enabling the traversal within and between regions. To the best of our knowledge, SURF is the first high genus 3D surface WSNs targeted and pure connectivitybased solution for linearizing the networks. It is fully distributed and highly scalable, requiring a nearly constant storage and communication cost per node in the network. Extensive simulations on several representative networks demonstrate that SURF works well on high genus 3D surface WSNs. I.
Distributed Information Storage and Retrieval in 3D Sensor Networks With General Topologies
"... Abstract—Distributed innetwork datacentric processing aims to reduce energy consumed for communication and establish a selfcontained data storage, retrieval, aggregation, and query sensor system that focuses more on the data itself rather than the identities of the individual network nodes. Doub ..."
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Abstract—Distributed innetwork datacentric processing aims to reduce energy consumed for communication and establish a selfcontained data storage, retrieval, aggregation, and query sensor system that focuses more on the data itself rather than the identities of the individual network nodes. Doublerulingbased schemes support efficient innetwork datacentric information storage and retrieval, especially for aggregated data, since all data with different types generated in a network can be conveniently retrieved along any single retrieval curve. Previous doublerulingbased research focuses on twodimensional (2D) wireless sensor networks where a 2D planar setting is assumed. With increasing interests in deploying wireless sensors in threedimensional (3D) space for various applications, it is urgent yet fundamentally challenging to design doublerulingbased approach in general 3D sensor networks because doublerulingbased schemes in general have much harder geometric constraints than other distributed innetwork datacentric processing schemes. In this research, we propose a geographic locationfree doublerulingbased approach for general 3D sensor networks with possibly complicated topology and geometric shapes. Without the knowledge of the geographic location and the distance bound, a query simply travels along a simple curve with the guaranteed success to retrieve aggregated data through time and space with one or different types across the network. Extensive simulations and comparisons show the proposed scheme with low cost and a balanced traffic load. Index Terms—3D sensor networks, datacentric, innetwork, information storage and retrieval. I.
1Distributed Information Storage and Retrieval in 3D Sensor Networks with General Topologies
"... Abstract—Distributed innetwork datacentric processing aims to reduce energy consumed for communication and establish a selfcontained data storage, retrieval, aggregation, and query sensor system which focuses more on the data itself rather than the identities of the individual network nodes. Dou ..."
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Abstract—Distributed innetwork datacentric processing aims to reduce energy consumed for communication and establish a selfcontained data storage, retrieval, aggregation, and query sensor system which focuses more on the data itself rather than the identities of the individual network nodes. Doubleruling based schemes support efficient innetwork datacentric information storage and retrieval, especially for aggregated data, since all data with different types generated in a network can be conveniently retrieved along any single retrieval curve. Previous doubleruling based research focuses on twodimensional (2D) wireless sensor networks where a 2D planar setting is assumed. With increasing interests in deploying wireless sensors in threedimensional (3D) space for various applications, it is urgent yet fundamentally challenging to design doubleruling based approach in general 3D sensor networks because doubleruling based schemes in general have much harder geometric constraints than other distributed innetwork datacentric processing schemes. In this research we propose a geographic location free doubleruling based approach for general 3D sensor networks with possibly complicated topology and geometric shapes. Without the knowledge of the geographic location and the distance bound, a query simply travels along a simple curve with the guaranteed success to retrieve aggregated data through time and space with one or different types across the network. Extensive simulations and comparisons show the proposed scheme with low cost and a balanced traffic load.
3D Surface Localization with Terrain Model
"... Abstract—The majority of current research on sensor network localization focuses on wireless sensor networks deployed on two dimensional (2D) plane or in three dimensional (3D) space, very few on 3D surface. However, many real world applications require largescale sensor networks deployed on the su ..."
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Abstract—The majority of current research on sensor network localization focuses on wireless sensor networks deployed on two dimensional (2D) plane or in three dimensional (3D) space, very few on 3D surface. However, many real world applications require largescale sensor networks deployed on the surface of a complex 3D terrain. Compared with planar and 3D network localizations, surface network localization generates unique and fundamental hardness. In this research, we explore 3D surface network localization with terrain model. A digital terrain model (DTM), available to public with a variable resolution up to one meter, is a 3D representation of a terrain’s surface. It is commonly built using remote sensing technology or from land surveying and can be easily converted to a triangular mesh. Given a sensor network deployed on the surface of a 3D terrain with onehop distance information available, we can extract a triangular mesh from the connectivity graph of the network. The constraint that the sensors must be on the known 3D terrain’s surface ensures that the triangular meshes of the network and the DTM of the terrain’s surface approximate the same geometric shape and overlap. We propose a fully distributed algorithm to construct a wellaligned mapping between the two triangular meshes. Based on this mapping, each sensor node of the network can easily locate reference grid points from the DTM to calculate its own geographic location. We carry out extensive simulations under various scenarios to evaluate the overall performance of the proposed localization algorithm. We also discuss the possibility of 3D surface network localization with mere connectivity and the results are promising. I.