Download or read book Adaptive Quantization and Distributed Estimation in Sensor Networks written by Kiran Sampath Kumar and published by . This book was released on 2014 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Distributed Estimation and Quantization Algorithms for Wireless Sensor Networks written by Sahar Movaghati and published by . This book was released on 2014 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: In distributed sensing systems, measurements from a random process or parameter are usually not available in one place. Also, the processing resources are distributed over the network. This distributed characteristic of such sensing systems demands for special attention when an estimation or inference task needs to be done. In contrast to a centralized case, where the raw measurements are transmitted to a fusion centre for processing, distributed processing resources can be used for some local processing, such as data compression or estimation according to distributed quantization or estimation algorithms. Wireless sensor networks (WSNs) consist of small sensor devices with limited power and processing capability, which cooperate through wireless transmission, in order to fulfill a common task. These networks are currently employed on land, underground, and underwater, in a wide range of applications including environmental sensing, industrial and structural monitoring, medical care, etc. However, there are still many impediments that hold back these networks from being pervasive, some of which are characteristics of WSNs, such as scarcity of energy and bandwidth resources and limited processing and storage capability of sensor nodes. Therefore, many challenges still need to be overcome before WSNs can be extensively employed. In this study, we concentrate on developing algorithms that are useful for estimation tasks in distributed sensing systems, such as wireless sensor networks. In designing these algorithms we consider the special constraints and characteristics of such systems, i.e., distributed nature of the measurements and the processing resources, as well as the limited energy of wireless and often small devices. We first investigate a general stochastic inference problem. We design a non-parametric algorithm for tracking a random process using distributed and noisy measurements. Next, we narrow down the problem to the distributed parameter estimation, and design distributed quantizers to compress measurement data while maintaining an accurate estimation of the unknown parameter. The contributions of this thesis are as follows. In Chapter 3, we design an algorithm for the distributed inference problem. We first use factor graphs to model the stochastic dependencies among the variables involved in the problem and factorize the global inference problem to a number of local dependencies. A message passing algorithm called the sum-product algorithm is then used on the factor graph to determine local computations and data exchanges that must be performed by the sensing devices in order to achieve the estimation goal. To tackle the nonlinearities in the problem, we combine the particle filtering and Monte-Carlo sampling in the sum-product algorithm and develop a distributed non-parametric solution for the general nonlinear inference problems. We apply our algorithm to the problem of distributed target tracking and show that even with a few number of particles the algorithm can efficiently track the target. In the next three chapters of the thesis, we focus on the distributed parameter quantization under energy limitations. In such problems, each sensor device sends a compressed version of its noisy observation of the same parameter to the fusion centre, where the parameter is estimated from the received data. In Chapter 4, we design a set of local quantizers that quantize each sensor's measurement to a few bits. We optimize the quantizers' design by maximizing the mutual information of the quantized data and the unknown parameter. At the fusion centre, we design the appropriate estimator that incorporates the compressed data from all sensors to estimate the parameter. For very stringent energy constraints, in Chapter 5, we focus on the binary quantization, where each sensor quantizes its data to exactly one bit. We find a set of local binary quantizers that jointly quantize the unknown variable with high precision. In the fusion centre, a maximum likelihood decoder is designed to estimate the parameter from the received bits. In Chapter 6, for an inhomogeneous scenario, where measurements have different signal-to-noise ratios, we find the best sensor-to-quantizer assignment that minimizes the estimation error, using the Hungarian algorithm.

Download or read book Distributed Fusion Estimation for Sensor Networks with Communication Constraints written by Wen-An Zhang and published by Springer. This book was released on 2016-05-27 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book systematically presents energy-efficient robust fusion estimation methods to achieve thorough and comprehensive results in the context of network-based fusion estimation. It summarizes recent findings on fusion estimation with communication constraints; several novel energy-efficient and robust design methods for dealing with energy constraints and network-induced uncertainties are presented, such as delays, packet losses, and asynchronous information... All the results are presented as algorithms, which are convenient for practical applications.

Download or read book Distributed Quantization estimation for Wireless Sensor Networks written by Alejandro Ribeiro and published by . This book was released on 2006 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Algorithms and Architectures for Parallel Processing written by Guojin Wang and published by Springer. This book was released on 2015-11-18 with total page 884 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Workshops and Symposiums of the 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015. The program of this year consists of 6 symposiums/workshops that cover a wide range of research topics on parallel processing technology: the Sixth International Workshop on Trust, Security and Privacy for Big Data, TrustData 2015; the Fifth International Symposium on Trust, Security and Privacy for Emerging Applications, TSP 2015; the Third International Workshop on Network Optimization and Performance Evaluation, NOPE 2015; the Second International Symposium on Sensor-Cloud Systems, SCS 2015; the Second International Workshop on Security and Privacy Protection in Computer and Network Systems, SPPCN 2015; and the First International Symposium on Dependability in Sensor, Cloud, and Big Data Systems and Applications, DependSys 2015. The aim of these symposiums/workshops is to provide a forum to bring together practitioners and researchers from academia and industry for discussion and presentations on the current research and future directions related to parallel processing technology. The themes and topics of these symposiums/workshops are a valuable complement to the overall scope of ICA3PP 2015 and give additional values and interests.

Download or read book Distributed Adaptive Estimation and Tracking Using Ad Hoc Wireless Sensor Networks written by Gonzalo Mateos Buckstein and published by . This book was released on 2009 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Building Sensor Networks written by Ioanis Nikolaidis and published by CRC Press. This book was released on 2017-11-22 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: For all the interest that wireless sensor networks have created over the past decade, there are few examples to show that they are truly delivering on this promise and anticipation. What is missing? Deviating from the usual focus on routing and energy efficiency, Building Sensor Networks: From Design to Applications attempts to stitch together the path from conceptual development of applications, on one end, to actual complete applications at the other. With this change in perspective, the book examines important facets of wireless sensor networks (WSNs) that are not often discussed in the literature. From Design Practices to the Networking Protocols that Glue Applications Together Organized into three sections, the book presents insights from international experts representing both industry and academia. The first section, on design practices, explores alternative ways to approach the tasks of developing a suitable WSN solution to an application and assisting that development in a manner that is not necessarily tied to a particular application. The second section, on networking protocols, illustrates the impact of the intermediaries—the "glue" of putting applications together. Chapters look at ways to address traffic, delays in network clustering, and the coexistence of a WSN with other systems on a frequency band. The final section of the book delves into experiences with applications in chemical sensing, defense, global trade and security, and ecosystem monitoring. Although these applications may fail the purist definition of an ideal WSN, they offer valuable lessons for the future development and deployment of WSNs. Challenge Your Thinking about Designing WSN Applications Emphasizing the need to build applications, the contributors present examples of what applications of WSNs could look like and identify the constraints. Throughout, the book challenges and illuminates your thinking about how to tame the complexity of designing a WSN application. It is essential reading for anyone interested in future wireless technologies.

Download or read book Adaptive Quantization in Wireless Sensor Networks with Encryption written by Niharika Konakalla and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book On Distributed Estimation for Resource Constrained Wireless Sensor Networks written by Alireza Sani and published by . This book was released on 2017 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: The accuracy of DES depends on many factors such as intensity of observation noises in sensors, quantization errors in sensors, available power and bandwidth of the network, quality of communication channels between sensors and the FC, and the choice of fusion rule in the FC. Taking into account all of these contributing factors and implementing a DES system which minimizes the MSE and satisfies all constraints is a challenging task. In order to probe into different aspects of this challenging task we identify and formulate the following three problems and address them accordingly:

Download or read book Analysis and Design of Networked Control Systems written by Keyou You and published by Springer. This book was released on 2015-01-03 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: · minimum data rate for stabilization of linear systems over noisy channels; · minimum network requirement for stabilization of linear systems over fading channels; and · stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are demonstrated. Analysis and Design of Networked Control Systems will interest control theorists and engineers working with networked systems and may also be used as a resource for graduate students with backgrounds in applied mathematics, communications or control who are studying such systems.

Download or read book Cognitive Systems and Signal Processing written by Fuchun Sun and published by Springer. This book was released on 2017-07-07 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Cognitive Systems and Signal Processing, ICCSIP2016, held in Beijing, China, in December 2016. The 59 revised full papers presented were carefully reviewed and selected from 171 submissions. The papers are organized in topical sections on Control and Decision; Image and Video; Machine Learning; Robotics; Cognitive System; Cognitive Signal Processing.

Download or read book Networked Multisensor Decision and Estimation Fusion written by Yunmin Zhu and published by CRC Press. This book was released on 2012-07-05 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Due to the increased capability, reliability, robustness, and survivability of systems with multiple distributed sensors, multi-source information fusion has become a crucial technique in a growing number of areas-including sensor networks, space technology, air traffic control, military engineering, agriculture and environmental engineering, and i

Download or read book Distributed Estimation Coding and Scheduling in Wireless Visual Sensor Networks written by Chao Yu and published by . This book was released on 2013 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: "In this thesis, we consider estimation, coding, and sensor scheduling for energy efficient operation of wireless visual sensor networks (VSN), which consist of battery-powered wireless sensors with sensing (imaging), computation, and communication capabilities. The competing requirements for applications of these wireless sensor networks (WSN) (e.g., smart environmental surveillance) include long duration of unattended operation and limited energy supply, which motivate our investigation into energy-efficient estimation, coding, and sensor scheduling to prolong the lifetime of these wireless networked systems. Motivated by a telepresence setting in visual sensor networks, we first consider an abstract setting for investigating efficient distributed estimation and coding in wireless sensor networks where the captured data is jointly Gaussian. The sensors are geographically dispersed, and acquire indirect, noisy observations pertaining to a desired signal. A central processor (CP) communicates with these sensors via a rate-constrained channel and estimates the desired signal. In a simplified scenario where information from one sensor is to be sent to the CP that already has information regarding the desired signal, we establish a decomposed structure for the optimal encoding of the local observation: a first pre-processing step to extract relevant information from the indirect observation with consideration of the side information, followed by a second step of side-informed encoding of the pre-processed output. In the general scenario consisting of multiple sensors, we present a sequential framework to recursively utilize the separation. Simulation results demonstrate that constructions obtained using the proposed decomposition offer very good performance, closely matching nonconstructive information theoretic bounds for the problem. We next propose a novel code construction and design method for low-density parity-check accumulate (LDPCA) codes used for rate-adaptive distributed source coding. We propose a code construction using non-uniform splitting, in contrast to the uniform splitting used in prior literature. We also develop methods to analyze the proposed LDPCA codes using density evolution, based on which code search strategies are developed to find good LDPCA codes. Simulation results show the proposed code design outperforms the conventional LDPCA code design, and provides state-of-the-art performance. The final part of the thesis addresses the networking aspect of VSNs, considering sensor scheduling and energy allocation in a telepresence wireless VSN application, where visual coverage over a monitored region is obtained by deploying image sensors (cameras). Each camera provides coverage over a part of the monitored region, and a CP coordinates these cameras in order to gather required visual data. We model the network lifetime as a stochastic random variable that depends upon the coverage geometry for the cameras and the distribution of data requests over the monitored region, two key characteristics that distinguish our problem from other WSN applications. By suitably abstracting this model of network lifetime and utilizing asymptotic analysis, we propose lifetime-maximizing camera scheduling and energy allocation strategies. The effectiveness of the proposed strategies is validated through simulations"--Page viii-ix.

Download or read book Networked Filtering and Fusion in Wireless Sensor Networks written by Magdi S. Mahmoud and published by CRC Press. This book was released on 2014-12-20 with total page 578 pages. Available in PDF, EPUB and Kindle. Book excerpt: By exploiting the synergies among available data, information fusion can reduce data traffic, filter noisy measurements, and make predictions and inferences about a monitored entity. Networked Filtering and Fusion in Wireless Sensor Networks introduces the subject of multi-sensor fusion as the method of choice for implementing distributed systems. The book examines the state of the art in information fusion. It presents the known methods, algorithms, architectures, and models of information fusion and discusses their applicability in the context of wireless sensor networks (WSNs). Paying particular attention to the wide range of topics that have been covered in recent literature, the text presents the results of a number of typical case studies. Complete with research supported elements and comprehensive references, this teaching-oriented volume uses standard scientific terminology, conventions, and notations throughout. It applies recently developed convex optimization theory and highly efficient algorithms in estimation fusion to open up discussion and provide researchers with an ideal starting point for further research on distributed estimation and fusion for WSNs. The book supplies a cohesive overview of the key results of theory and applications of information-fusion-related problems in networked systems in a unified framework. Providing advanced mathematical treatment of fundamental problems with information fusion, it will help you broaden your understanding of prospective applications and how to address such problems in practice. After reading the book, you will gain the understanding required to model parts of dynamic systems and use those models to develop distributed fusion control algorithms that are based on feedback control theory.

Download or read book Distributed Sensor Networks written by S. Sitharama Iyengar and published by CRC Press. This book was released on 2022-06-01 with total page 1679 pages. Available in PDF, EPUB and Kindle. Book excerpt: The best-selling Distributed Sensor Networks became the definitive guide to understanding this far-reaching technology. Preserving the excellence and accessibility of its predecessor, Distributed Sensor Networks, Second Edition once again provides all the fundamentals and applications in one complete, self-contained source. Ideal as a tutorial for students or as research material for engineers, the book gives readers up-to-date, practical insight on all aspects of the field.This two volume set, this second edition has been revised and expanded with over 500 additional pages and more than 300 new illustrations. This edition incorporates contributions from many veterans of the DARPA ISO SENSIT program as well as new material from distinguished researchers in the field. It offers 13 fully revised chapters and 22 new chapters, covering new perspectives on information fusion, the latest technical developments, and current sensor network applications. Volume 1 Image and Sensor Signal Processing includes: Distributed Sensing and Signal Processing; Information Fusion; and Power Management. Volume 2 Sensor Networking and Applications includes: Sensor Deployment; Adaptive Tasking; Self-Configuration; System Control; and Engineering Examples.

Download or read book Wireless Algorithms Systems and Applications written by Xinbing Wang and published by Springer. This book was released on 2012-08-10 with total page 762 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Wireless Algorithms, Systems, and Applications, WASA 2012, held in Yellow Mountains, China, in August 2012. The 24 revised full papers presented together with 32 invited papers were carefully reviewed and selected from 116 submissions. The papers cover a wide range of topics such as cognitive radio networks, cyber-physical network systems, mobile handset networking systems, underwater and radar wireless networks, and wireless and mobile security.

Download or read book Optimal Distributed Detection and Estimation in Static and Mobile Wireless Sensor Networks written by Xusheng Sun and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation develops optimal algorithms for distributed detection and estimation in static and mobile sensor networks. In distributed detection or estimation scenarios in clustered wireless sensor networks, sensor motes observe their local environment, make decisions or quantize these observations into local estimates of finite length, and send/relay them to a Cluster-Head (CH). For event detection tasks that are subject to both measurement errors and communication errors, we develop an algorithm that combines a Maximum a Posteriori (MAP) approach for local and global decisions with low-complexity channel codes and processing algorithms. For event estimation tasks that are subject to measurement errors, quantization errors and communication errors, we develop an algorithm that uses dithered quantization and channel compensation to ensure that each mote's local estimate received by the CH is unbiased and then lets the CH fuse these estimates into a global one using a Best Linear Unbiased Estimator (BLUE). We then determine both the minimum energy required for the network to produce an estimate with a prescribed error variance and show how this energy must be allocated amongst the motes in the network. In mobile wireless sensor networks, the mobility model governing each node will affect the detection accuracy at the CH and the energy consumption to achieve this level of accuracy. Correlated Random Walks (CRWs) have been proposed as mobility models that accounts for time dependency, geographical restrictions and nonzero drift. Hence, the solution to the continuous-time, 1-D, finite state space CRW is provided and its statistical behavior is studied both analytically and numerically. The impact of the motion of sensor on the network's performance is also studied.