Performance Evaluation Of Minimum Mean Square Error Based Secure Localization Protocols For Wireless Sensor Networks
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Performance Evaluation Of Minimum Mean Square Error Based Secure Localization Protocols For Wireless Sensor Networks
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Author : Hamsatharini Jeganathan
language : en
Publisher:
Release Date : 2008
Performance Evaluation Of Minimum Mean Square Error Based Secure Localization Protocols For Wireless Sensor Networks written by Hamsatharini Jeganathan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Wireless sensor networks categories.
Dissertation Abstracts International
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Author :
language : en
Publisher:
Release Date : 2008
Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Dissertations, Academic categories.
Secure Localization And Time Synchronization For Wireless Sensor And Ad Hoc Networks
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Author : Radha Poovendran
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-12-03
Secure Localization And Time Synchronization For Wireless Sensor And Ad Hoc Networks written by Radha Poovendran and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-12-03 with Technology & Engineering categories.
Localization is a critical process in mobile ad hoc networks and wireless sensor networks. Wireless sensor node or MANET devices need to know the network's location or its relative location, with respect to the rest of the network neighbors. However, due to the open spectrum nature of wireless communication, it is subject to attacks and intrusions. Hence the wireless network synchronization needs to be both robust and secure. Furthermore, issues such as energy constraints and mobility make the localization process even more challenging. Secure Localization and Time Synchronization for Wireless Sensor and Ad Hoc Networks presents the latest research results in the area of secure localization for both wireless mobile ad hoc networks and wireless sensor networks.
Interference Mitigation With Selective Retransmissions In Wireless Sensor Networks
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Author : Selig, Marc
language : en
Publisher: kassel university press GmbH
Release Date : 2016
Interference Mitigation With Selective Retransmissions In Wireless Sensor Networks written by Selig, Marc and has been published by kassel university press GmbH this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
A wireless sensor network with single-antenna sensors on the transmitter side and an access point (AP) equipped with multiple antennas on the receiver side is considered. In order to reduce the number of outages resulting from the noise amplification by the linear reconstruction within the successive interference cancellation (SIC) procedure, the AP is given the possibility to request retransmissions of signals from selected sensors in a subsequent time slot (TS). In case retransmissions are needed also in the subsequent time slot, the AP postpones the signal detection until all requested signals have been retransmitted making the signal detection a recursive procedure. The number of sensors required to retransmit depends on the order of the processed sensor signals within the SIC procedure. We propose an optimal algorithm based on a QR-decomposition and a depth-first search through all possible decoding orders, which finds the decoding order necessitating a minimum number of retransmissions suitable for zero-forcing (ZF) and minimum mean square error (MMSE) linear reconstruction approaches. Since the computational complexity of the optimal algorithm is high, different suboptimal algorithms with lower computational complexity are proposed for the case of ZFSIC and MMSE-SIC, respectively. The recursive nature of the retransmission procedure may lead to an unlimited detection delay, because the linear reconstruction followed by SIC starts only when no sensor needs a retransmission from the previous TS. By reducing the number of transmitting sensors for a fixed number of receiving antennas the receive diversity of the AP can be exploited, which leads to less retransmissions. Therefore, we propose an optimal transmit policy, which selects the best set of sensors to maximize the system throughput. This optimal transmit policy is found by means of a Markov decision process in combination with dynamic programming.
Rss Aoa Based Target Localization And Tracking In Wireless Sensor Networks
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Author : Slavisa Tomic
language : en
Publisher: CRC Press
Release Date : 2022-09-01
Rss Aoa Based Target Localization And Tracking In Wireless Sensor Networks written by Slavisa Tomic and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-01 with Science categories.
The desire for precise knowledge about the location of a moving object at any time instant has motivated a great deal of scientific research recently. This is owing to a steady expansion of the range of enabling devices and technologies, as well as the need for seamless solutions for location-based services. Besides localization accuracy, a common requirement for emerging solutions is that they are cost-abstemious, both in terms of the financial and computational cost. Hence, development of localization strategies from already deployed technologies, e.g., from different terrestrial radio frequency sources is of great practical interest. Amongst other, these include localization strategies based on received signal strength (RSS), time of arrival, angle of arrival (AoA) or a combination of them. RSS-AoA-based Target Localization and Tracking in Wireless Sensor Networks presents recent advances in developing algorithms for target localization and tracking, reflecting the state-of-the-art algorithms and research achievements in target localization and tracking based on hybrid (RSS-AoA) measurements.Technical topics discussed in the book include:Centralized RSS-AoA-based Target LocalizationDistributed RSS-AoA-based Target LocalizationRSS-AoA-based Target Tracking via Maximum A Posteriori EstimatorRSS-AoA-based Target Tracking via Kalman FilterRSS-AoA-based via Sensor NavigationThis book is of interest for personnel in telecommunications and surveillance industries, military, smart systems, as well as academic staff and postgraduate/research students in telecommunications, signal processing, and non-smooth and convex optimization.
Modeling And Multi Objective Optimization For Energy Based Target Localization Using Wireless Sensor Networks
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Author : Zhenxing Luo
language : en
Publisher:
Release Date : 2012
Modeling And Multi Objective Optimization For Energy Based Target Localization Using Wireless Sensor Networks written by Zhenxing Luo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with Wireless sensor networks categories.
This dissertation focuses on energy-based target localization in wireless sensor networks (WSNs). A WSN consists of a fusion center and a large number of sensors. The fusion center localizes a target using a maximum likelihood estimation (MLE) method based on decisions received from sensors whose positions are known. However, several factors may degrade localization performance, including imperfect communication channels, sensor faults, sensor position uncertainty, and sensor sleep. Localization performance may be improved if these factors are accounted for in the MLE framework. In this dissertation, models were developed that describe how localization performance is affected by imperfect communication channels, multi-hop communication channels, sensor position uncertainty, sensor faults, and sensor sleep. These models were incorporated into the MLE framework either simultaneously or separately. The Cramer-Rao lower bound on the estimation error (CRLB) was also derived. Simulation results showed that the new MLE methods gave better localization performance in terms of root mean square (RMS) estimation errors than current methods which ignore these factors that degrade localization performance. Moreover, the RMS estimation errors were close to the CRLB. Based on the sensor sleep model, an energy saving strategy was developed in which the sensor sleep probability is used to adjust energy consumption of the WSN. However, although the sensor sleep strategy saves energy, sleeping sensors cannot send decisions to the fusion center and missing decisions can degrade localization performance. Therefore, the system design must consider tradeoffs between energy consumption and localization performance. Models of energy consumption and localization performance were developed for one-dimensional and two-dimensional sensor arrays. These models were used in a multi-objective optimization method that balances energy consumption and localization performance. The Pareto-fronts generated by the multi-objective optimization method allow the system designer to make tradeoffs between energy consumption and localization performance.
Resilient Data Aggregation In Wireless Sensor Networks
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Author :
language : en
Publisher:
Release Date : 2004
Resilient Data Aggregation In Wireless Sensor Networks written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with categories.
Sensor nodes are low-cost and low-power devices that are prone to node compromises, communication failures and malfunctioning of sensing hardware. As a result, some nodes may report outlying data values, introducing significant deviations in the aggregated sensor readings. This thesis presents a practical resilient outlier detection technique to filter out the influence of the outlying data reported by faulty or compromised nodes. The proposed outlier detection algorithm is based on event localization using minimum mean squared error (MMSE) estimation combined with threshold-based consistency checking to detect outliers. Data aggregation is one of the key techniques commonly used to develop lightweight communication protocols applicable to wireless sensor networks. The proposed approach handles localization of multiple events by grouping the sensor readings into spatially correlated clusters and performing an event-centric detection of outliers. In the entire process of data aggregation, the outlier detection technique fits as a preprocessing stage for reducing the effect of outliers on the aggregated result. Suitable extensions to the basic outlier detection algorithm are proposed to effectively apply the algorithm to both centralized and decentralized sensor network architectures. This thesis further includes studies that test the effectiveness of the proposed approach, including the detection rate, the false positive rate, degree of damage and the resilience to malicious readings introduced by the attackers. The experimental results show that on average the proposed approach detects as high as 80-90% of the outliers while resulting in 5-15% false positive rate when the network consists of 40-45% outliers. The experiments also show that the extent of damage on the aggregated result is below 50% due to the elimination of outliers before aggregation. Finally, the resilient data aggregation process requires modest computational and memory requirements with zero commu.
Localization Algorithms And Strategies For Wireless Sensor Networks Monitoring And Surveillance Techniques For Target Tracking
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Author : Mao, Guoqiang
language : en
Publisher: IGI Global
Release Date : 2009-05-31
Localization Algorithms And Strategies For Wireless Sensor Networks Monitoring And Surveillance Techniques For Target Tracking written by Mao, Guoqiang and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-31 with Computers categories.
Wireless localization techniques are an area that has attracted interest from both industry and academia, with self-localization capability providing a highly desirable characteristic of wireless sensor networks. Localization Algorithms and Strategies for Wireless Sensor Networks encompasses the significant and fast growing area of wireless localization techniques. This book provides comprehensive and up-to-date coverage of topics and fundamental theories underpinning measurement techniques and localization algorithms. A useful compilation for academicians, researchers, and practitioners, this Premier Reference Source contains relevant references and the latest studies emerging out of the wireless sensor network field.
A Distributed Cooperative Algorithm For Localization In Wireless Sensor Networks Using Gaussian Mixture Modeling
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Author : Tashnim Jabir Shovon Chowdhury
language : en
Publisher:
Release Date : 2016
A Distributed Cooperative Algorithm For Localization In Wireless Sensor Networks Using Gaussian Mixture Modeling written by Tashnim Jabir Shovon Chowdhury and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Computer algorithms categories.
Wireless sensor networks are defined as spatially distributed autonomous sensors to monitor certain physical or environmental conditions like temperature, pressure, sound, etc. and incorporate the collected data to pass to a central location through a network. Multifarious applications including cyber-physical systems, military, eHealth, environmental monitoring, weather forecasting, etc. make localization a crucial part of wireless sensor networks. Since accuracy and low computational time of the localization, in case of some applications like emergency police or medical services, is very important, the main objective of any localization algorithm should be to attain more accurate and less time consuming scheme. This thesis presents a cooperative sensor network localization scheme that approximates measurement error statistics by Gaussian mixture. Expectation Maximization (EM) algorithm has been implemented to approximate maximum-likelihood estimator of the unknown sensor positions and Gaussian mixture model (GMM) parameters. To estimate the sensor positions we have adopted several algorithms including Broyden-Fletcher-Goldfarb-Shanno (BFGS) Quasi-Newton (QN), Davidon-Fletcher-Powell (DFP), and Cooperative Least Square (LS) algorithm. The distributive form of the algorithms meet the scalability requirements of sparse sensor networks. The algorithms have been analyzed for different number of network sizes. Cramer Rao Lower Bound (CRLB) has been presented and utilized to evaluate the performance of the algorithms. Through Monte Carlo simulation we show the superior performance of BFGS-QN over DFP and cooperative LS in terms of localization accuracy. Moreover the results demonstrate that Root Mean Square Error (RMSE) of BFGS-QN is closer to derived CRLB than both DFP and cooperative LS.
Security And Robustness Of Localization Techniques For Emergency Sensor Networks
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Author : Murtuza Shabbir Jadliwala
language : en
Publisher:
Release Date : 2008
Security And Robustness Of Localization Techniques For Emergency Sensor Networks written by Murtuza Shabbir Jadliwala and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
Recent advancement in radio and processor technology has seen the rise of Wireless Sensor Networks (WSN) as a reliable and cost-effective tool for real-time information gathering and analysis tasks during emergency scenarios like natural disasters, terrorist attacks, military conflicts, etc. Post-deployment localization is extremely important and necessary in these applications. But, current distributed localization approaches are not designed for such highly hostile and dynamic network conditions. This dissertation studies the adverse effects of factors like cheating behavior, node disablement and measurement inconsistencies on the corresponding localization protocols and attempts to provide simple and efficient solutions in order to overcome these problems. The first problem addressed in this dissertation is, how to perform efficient distance-based localization in the presence of cheating beacon nodes? This dissertation attempts to answer two fundamental questions in distance-based localization: (i) In the presence of cheating beacons, what are the necessary and sufficient conditions to guarantee a bounded localization error? and (ii) Under these conditions, what class of algorithms can provide that error bound? In this part of the dissertation, it is shown that when the number of cheating beacons is greater than or equal to some threshold, there is no localization algorithm that can guarantee a bounded error. Furthermore, it is also proved that when the number of malicious beacons is below that threshold, a non-empty class of bounded error localization algorithms can be identified. Two secure distance-based localization algorithms are outlined and their performance is verified using simulation experiments. The next part of the dissertation underscores the lack of fault-tolerance in existing localization protocols and proposes simple mechanisms to overcome this problem. Sensor node disablement adversely affects the overall node deployment distribution and the efficiency of localization techniques that depend on this distribution, for example, signature-based techniques. In order to improve the fault-tolerance in these schemes, it is important to first construct a probabilistic model for node disablement. In this direction, the phenomenon of sensor node disablement is modeled as a stochastic time process. A novel deployment strategy that non-uniformly deploys sensor nodes over the monitored area is also outlined. Then, a fault-tolerance related improvement to existing localization schemes is proposed, which discards observations from unhealthy groups of nodes during the localization process. In order to overcome the complexity concerns, a simple signature-based technique, called ASFALT, is also proposed. ASFALT estimates the target location by first predicting distances to known location references using the underlying node distribution and a simple averaging argument. Extensive measurements from simulation experiments verify the fault-tolerance and performance of the proposed solutions. In the final part of this dissertation, the problem of efficiently mitigating inconsistencies in location-based applications is addressed. Inconsistencies in location information, caused by cheating behavior or measurement errors can be modeled using a weighted, undirected graph and a cheating location function that can assign incorrect locations to the nodes or a cheating (but verifiable) distance function that can assign inconsistent distances to edges. In either case, an edge relation where the assigned edge distance is not within some very small factor of the Euclidean distance between the connecting nodes represents some inconsistency and is referred to as an inconsistent edge. The problem of efficiently mitigating location inconsistencies in the network can then be formulated as an optimization problem that determines the largest induced subgraph (obtained by eliminating a subset of vertices) containing only consistent edges. Two optimization problems can be stated. The first maximizes the number of vertices in the consistent subgraph, while the second maximizes the number of consistent edges in the consistent subgraph. Combinatorial properties including hardness and approximation ratio for these problems are studied and intelligent solution strategies are proposed. A comparative analysis that verifies the practical efficiency of these algorithms by using measurements from simulation experiments is also presented.