Virtual and topological coordinate based routing, mobility tracking and prediction in 2D and 3D wireless sensor networks

2013 Fall.Includes bibliographical references.A Virtual Coordinate System (VCS) for Wireless Sensor Networks (WSNs) characterizes each sensor node's location using the minimum number of hops to a specific set of sensor nodes called anchors. VCS does not require geographic localization hardware such as Global Positioning System (GPS), or localization algorithms based on Received Signal Strength Indication (RSSI) measurements. Topological Coordinates (TCs) are derived from Virtual Coordinates (VCs) of networks using Singular Value Decomposition (SVD). Topology Preserving Maps (TPMs) based on TCs contain 2D or 3D network topology and directional information that are lost in VCs. This thesis extends the scope of VC and TC based techniques to 3D sensor networks and networks with mobile nodes. Specifically, we apply existing Extreme Node Search (ENS) for anchor placement for 3D WSNs. 3D Geo-Logical Routing (3D-GLR), a routing algorithm for 3D sensor networks that alternates between VC and TC domains is evaluated. VC and TC based methods have hitherto been used only in static networks. We develop methods to use VCs in mobile networks, including the generation of coordinates, for mobile sensors without having to regenerate VCs every time the topology changes. 2D and 3D Topological Coordinate based Tracking and Prediction (2D-TCTP and 3D-TCTP) are novel algorithms developed for mobility tracking and prediction in sensor networks without the need of physical distance measurements. Most existing 2D sensor networking algorithms fail or perform poorly in 3D networks. Developing VC and TC based algorithms for 3D sensor networks is crucial to benefit from the scalability, adjustability and flexibility of VCs as well as to overcome the many disadvantages associated with geographic coordinate systems. Existing ENS algorithm for 2D sensor networks plays a key role in providing a good anchor placement and we continue to use ENS algorithm for anchor selection in 3D network. Additionally, we propose a comparison algorithm for ENS algorithm named Double-ENS algorithm which uses two independent pairs of initial anchors and thereby increases the coverage of ENS anchors in 3D networks, in order to further prove if anchor selection from original ENS algorithm is already optimal. Existing Geo-Logical Routing (GLR) algorithm demonstrates very good routing performance by switching between greedy forwarding in virtual and topological domains in 2D sensor networks. Proposed 3D-GLR extends the algorithm to 3D networks by replacing 2D TCs with 3D TCs in TC distance calculation. Simulation results show that the 3D-GLR algorithm with ENS anchor placement can significantly outperform current Geographic Coordinates (GCs) based 3D Greedy Distributed Spanning Tree Routing (3D-GDSTR) algorithm in various network environments. This demonstrates the effectiveness of ENS algorithm and 3D-GLR algorithm in 3D sensor networks. Tracking and communicating with mobile sensors has so far required the use of localization or geographic information. This thesis presents a novel approach to achieve tracking and communication without geographic information, thus significantly reducing the hardware cost and energy consumption. Mobility of sensors in WSNs is considered under two scenarios: dynamic deployment and continuous movement. An efficient VC generation scheme, which uses the average of neighboring sensors' VCs, is proposed for newly deployed sensors to get coordinates without flooding based VC generation. For the second scenario, a prediction and tracking algorithm called 2D-TCTP for continuously moving sensors is developed for 2D sensor networks. Predicted location of a mobile sensor at a future time is calculated based on current sampled velocity and direction in topological domain. The set of sensors inside an ellipse-shaped detection area around the predicted future location is alerted for the arrival of mobile sensor for communication or detection purposes. Using TPMs as a 2D guide map, tracking and prediction performances can be achieved similar to those based on GCs. A simple modification for TPMs generation is proposed, which considers radial information contained in the first principle component from SVD. This modification improves the compression or folding at the edges that has been observed in TPMs, and thus the accuracy of tracking. 3D-TCTP uses a detection area in the shape of a 3D sphere. 3D-TCTP simulation results are similar to 2D-TCTP and show competence comparable to the same algorithms based on GCs although without any 3D geographic information

Virtual coordinate based techniques for wireless sensor networks: a simulation tool and localization & planarization algorithms

2013 Summer.Includes bibliographical references.Wireless sensor Networks (WSNs) are deployments of smart sensor devices for monitoring environmental or physical phenomena. These sensors have the ability to communicate with other sensors within communication range or with a base station. Each sensor, at a minimum, comprises of sensing, processing, transmission, and power units. This thesis focuses on virtual coordinate based techniques in WSNs. Virtual Coordinates (VCs) characterize each node in a network with the minimum hop distances to a set of anchor nodes, as its coordinates. It provides a compelling alternative to some of the localization applications such as routing. Building a WSN testbed is often infeasible and costly. Running real experiments on WSNs testbeds is time consuming, difficult and sometimes not feasible given the scope and size of applications. Simulation is, therefore, the most common approach for developing and testing new protocols and techniques for sensor networks. Though many general and wireless sensor network specific simulation tools are available, no available tool currently provides an intuitive interface or a tool for virtual coordinate based simulations. A simulator called VCSIM is presented which focuses specifically on Virtual Coordinate Space (VCS) in WSNs. With this simulator, a user can easily create WSNs networks of different sizes, shapes, and distributions. Its graphical user interface (GUI) facilitates placement of anchors and generation of VCs. Localization in WSNs is important for several reasons including identification and correlation of gathered data, node addressing, evaluation of nodes' density and coverage, geographic routing, object tracking, and other geographic algorithms. But due to many constraints, such as limited battery power, processing capabilities, hardware costs, and measurement errors, localization still remains a hard problem in WSNs. In certain applications, such as security sensors for intrusion detection, agriculture, land monitoring, and fire alarm sensors in a building, the sensor nodes are always deployed in an orderly fashion, in contrast to random deployments. In this thesis, a novel transformation is presented to obtain position of nodes from VCs in rectangular, hexagonal and triangular grid topologies. It is shown that with certain specific anchor placements, a location of a node can be accurately approximated, if the length of a shortest path in given topology between a node and anchors is equal to length of a shortest path in full topology (i.e. a topology without any voids) between the same node and anchors. These positions are obtained without the need of any extra localization hardware. The results show that more than 90% nodes were able to identify their position in randomly deployed networks of 80% and 85% node density. These positions can then be used for deterministic routing which seems to have better avg. path length compared to geographic routing scheme called "Greedy Perimeter Stateless Routing (GPSR)". In many real world applications, manual deployment is not possible in exact regular rectangular, triangular or hexagonal grids. Due to placement constraint, nodes are often placed with some deviation from ideal grid positions. Because of placement tolerance and due to non-isotropic radio patterns nodes may communicate with more or less number of neighbors than needed and may form cross-links causing non-planar topologies. Extracting planar graph from network topologies is known as network planarization. Network planarization has been an important technique in numerous sensor network protocols--such as GPSR for efficient routing, topology discovery, localization and data-centric storage. Most of the present planarization algorithms are based on location information. In this thesis, a novel network planarization algorithm is presented for rectangular, hexagonal and triangular topologies which do not use location information. The results presented in this thesis show that with placement errors of up to 30%, 45%, and 30% in rectangular, triangular and hexagonal topologies respectively we can obtain good planar topologies without the need of location information. It is also shown that with obtained planar topology more nodes acquire unique VCs

Enhanced Topology Aware Routing for WSN

In this paper Enhanced Topology Aware Routing (ETAR) is proposed for point to point routing in wireless sensor network. Each node is characterized by a coordinate vector consisting of the shortest path hop distances to a subset of nodes, named anchors. The ETAR algorithm efficiently maps a network topology into a low-dimensional virtual coordinate space where hop distances between pairwise nodes are preserved. It assist greedy forwarding to find the right neighbor that is one hop closer to the destination by eliminating the local minimum problem and achieve high success ratio of packet delivery and throughput without location informatio

EEGRA: Energy Efficient Geographic Routing Algorithms for Wireless Sensor Network

[[abstract]]Energy efficiency is critical in wireless sensor networks (WSN) for system reliability and deployment cost. The power consumption of the communication in multi-hop WSN is primarily decided by three factors: routing distance, signal interference, and computation cost of routing. Several routing algorithms designed for energy efficiency or interference avoidance had been proposed. However, they are either too complex to be useful in practices or specialized for certain WSN architectures. In this paper, we propose two energy efficient geographic routing algorithms (EEGRA) for wireless sensor networks, which are based on existing geographic routing algorithms and take all three factors into account. The first algorithm combines the interference into the routing cost function, and uses it in the routing decision. The second algorithm transforms the problem into a constrained optimization problem, and solves it by searching the optimal discretized interference level. We integrate four geographic routing algorithms: GOAFR+, Face Routing, GPSR, and RandHT, to both EEGRA algorithms and compare them with three other routing methods in terms of power consumption and computation cost for the grid and irregular sensor topologies. The results of our experiments show both algorithms conserve sensor’s routing energy 30% ~ 50% comparing to general geographic routing algorithms. In addition, the time complexity of EEGRA algorithms is similar to the geographic greedy routing methods, which is much faster than the optimal SINR-based algorithm.[[conferencetype]]國際[[conferencedate]]20121213~20121215[[iscallforpapers]]Y[[conferencelocation]]San Marcos, Texas, US

Data and resource management in wireless networks via data compression, GPS-free dissemination, and learning

“This research proposes several innovative approaches to collect data efficiently from large scale WSNs. First, a Z-compression algorithm has been proposed which exploits the temporal locality of the multi-dimensional sensing data and adapts the Z-order encoding algorithm to map multi-dimensional data to a one-dimensional data stream. The extended version of Z-compression adapts itself to working in low power WSNs running under low power listening (LPL) mode, and comprehensively analyzes its performance compressing both real-world and synthetic datasets. Second, it proposed an efficient geospatial based data collection scheme for IoTs that reduces redundant rebroadcast of up to 95% by only collecting the data of interest. As most of the low-cost wireless sensors won’t be equipped with a GPS module, the virtual coordinates are used to estimate the locations. The proposed work utilizes the anchor-based virtual coordinate system and DV-Hop (Distance vector of hops to anchors) to estimate the relative location of nodes to anchors. Also, it uses circle and hyperbola constraints to encode the position of interest (POI) and any user-defined trajectory into a data request message which allows only the sensors in the POI and routing trajectory to collect and route. It also provides location anonymity by avoiding using and transmitting GPS location information. This has been extended also for heterogeneous WSNs and refined the encoding algorithm by replacing the circle constraints with the ellipse constraints. Last, it proposes a framework that predicts the trajectory of the moving object using a Sequence-to-Sequence learning (Seq2Seq) model and only wakes-up the sensors that fall within the predicted trajectory of the moving object with a specially designed control packet. It reduces the computation time of encoding geospatial trajectory by more than 90% and preserves the location anonymity for the local edge servers”--Abstract, page iv

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Cross-layer Optimized Wireless Video Surveillance

A wireless video surveillance system contains three major components, the video capture and preprocessing, the video compression and transmission over wireless sensor networks (WSNs), and the video analysis at the receiving end. The coordination of different components is important for improving the end-to-end video quality, especially under the communication resource constraint. Cross-layer control proves to be an efficient measure for optimal system configuration. In this dissertation, we address the problem of implementing cross-layer optimization in the wireless video surveillance system. The thesis work is based on three research projects. In the first project, a single PTU (pan-tilt-unit) camera is used for video object tracking. The problem studied is how to improve the quality of the received video by jointly considering the coding and transmission process. The cross-layer controller determines the optimal coding and transmission parameters, according to the dynamic channel condition and the transmission delay. Multiple error concealment strategies are developed utilizing the special property of the PTU camera motion. In the second project, the binocular PTU camera is adopted for video object tracking. The presented work studied the fast disparity estimation algorithm and the 3D video transcoding over the WSN for real-time applications. The disparity/depth information is estimated in a coarse-to-fine manner using both local and global methods. The transcoding is coordinated by the cross-layer controller based on the channel condition and the data rate constraint, in order to achieve the best view synthesis quality. The third project is applied for multi-camera motion capture in remote healthcare monitoring. The challenge is the resource allocation for multiple video sequences. The presented cross-layer design incorporates the delay sensitive, content-aware video coding and transmission, and the adaptive video coding and transmission to ensure the optimal and balanced quality for the multi-view videos. In these projects, interdisciplinary study is conducted to synergize the surveillance system under the cross-layer optimization framework. Experimental results demonstrate the efficiency of the proposed schemes. The challenges of cross-layer design in existing wireless video surveillance systems are also analyzed to enlighten the future work. Adviser: Song C

Emerging Communications for Wireless Sensor Networks

Wireless sensor networks are deployed in a rapidly increasing number of arenas, with uses ranging from healthcare monitoring to industrial and environmental safety, as well as new ubiquitous computing devices that are becoming ever more pervasive in our interconnected society. This book presents a range of exciting developments in software communication technologies including some novel applications, such as in high altitude systems, ground heat exchangers and body sensor networks. Authors from leading institutions on four continents present their latest findings in the spirit of exchanging information and stimulating discussion in the WSN community worldwide