Kayhan Eritmen · Sabanci University · 2008
Wireless Sensor Networks (WSNs) have recently attracted a lot of attention in various potential applications in military, health, environment and commerce due to their detection, processing and communication capabilities. In this thesis, we consider distributed detection problem for both parallel and hierarchical topology in which sensor decisions are sent over non-ideal wireless channels. We first investigate optimal fusion rules in Neyman-Pearson sense for all considered network configuration. We then, suggest suboptimal fusion rules to decrease computational complexity of the optimal fusion rules. Thirdly, multi-bit distributed detection is investigated both analytically and numerically to increase the detection performance. Finally, we propose fusion center diversity by employing multiple antennas at the fusion center to improve the detection performance of the network and derive optimum fusion rules accordingly. Simulation results suggest that fusion center diversity increases the probability of detection for a given constant false alarm probability.
Cited by 0
Hongbing Cao, Qi Huang, Zhiqiang Liang et al. · 2006
This paper considers the problem of detecting ground moving targets in a wireless sensor network for military surveillance application. The sensor nodes are severely constrained in both power and computational performance, and the battle field environments are commonly very complicated. A modified order statistic constant false alarm rate (OS-CFAR) detection algorithm was chosen to be implemented on sensor nodes. The algorithm includes background estimate and adaptive threshold. The experimental results with real acoustic and seismic data indicate that this algorithm is robust and flexible.
Cited by 2
2010
The following topics are dealt with: broadband, wireless computing, communication and applications; ad hoc networks; sensor networks; parallel and multi-core systems; mesh networks; practical security and privacy application; optical networks; networks algorithms and protocols; distributed schemes and protocols; wireless networks; disaster information systems; network security, privacy and trust; distributed algorithms and systems; multimedia and Web applications; wireless communication; digital signature; computer forensics; authentication and privacy; cloud and wireless security; image secret, sensor network and computer security; fault detection and diagnosis; intelligent networks; human behavior understanding; image and video analysis; scattering and diffraction; wireless modelling; wireless technologies; wireless traffic control and resource allocation; intelligent algorithms; network performance analysis; network services; teleoperation and robot control; robotics; agent technology and multiagent systems; symbolic computing; and wireless sensor networks protocols.
Cited by 0
Yingbo Hua, Yi Huang · 2015
For large-scale multi-hop wireless sensor networks, progressive es-timation and detection algorithms are developed. For progressive estimation, the classical principles of best linear unbiased estimation (BLUE) and linear minimum mean square error (LMMSE) estima-tion are applied. The difference and similarity between the two are revealed. For progressive detection, a tradeoff between detection performance and limited decision propagation is studied. The pro-gressive estimation and detection algorithms are distributed and per-formed at the application layer of wireless sensor networks, which are fully adaptive to the operations at the networking and other lower layers which can be designed for high spectral efficiency. Index Terms — Progressive estimation and detection, distrib-uted estimation and detection, wireless sensor networks, large-scale multi-hop networks 1.
Cited by 0
Zhi-li Zhang, Don Towsley · 2015
Graduated with highest distinction. RESEARCH INTERESTS General: Computer and telecommunication networks, Internet quality of service and novel architectures, wireless networks, sensor networks, multimedia networking, peer-to-peer and distributed systems, network security. Current Focus: Internet inter- and intra-domain routing, wireless ad hoc routing, routing algorithms and architectures for heterogeneous networks, distributed sensor networks, resilient large-scale distributed system design, self-organizing and peer-to-peer systems, security attack detection and prevention, secure networked system design.
Cited by 0
Hongli Dong, Zidong Wang, Steven X. Ding et al. · Mathematical Problems in Engineering · 2014
In recent years, theoretical and practical research on large‐scale networked systems has gained an increasing attention from multiple disciplines including engineering, computer science, and mathematics. Lying in the core part of the area are the distributed estimation and fault detection problems that have recently been attracting growing research interests. In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. In this paper, a bibliographical review is provided on distributed filtering and fault detection problems over sensor networks. The algorithms employed to study the distributed filtering and detection problems are categorised and then discussed. In addition, some recent advances on distributed detection problems for faulty sensors and fault events are also summarized in great detail. Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks.
Cited by 84Open access
Georg Wittenburg, Norman Dziengel, Stephan Adler et al. · IEEE Communications Magazine · 2012
Event detection in wireless sensor networks is a sophisticated method for processing sampled data directly on the sensor nodes, thereby reducing the need for multihop communication with the base station of the network. In contrast to application-agnostic compression or aggregation techniques, event detection pushes application-level knowledge into the network. In-network event detection - especially the distributed form involving multiple sensor nodes - has thus an exceptional potential to increase energy efficiency, thus prolonging the lifetime of the network. In this article, we summarize recently proposed system architectures and algorithms employed for event detection in wireless sensor networks. On the example of the AVS-Extrem platform, we illustrate how energy-efficient event detection can be implemented through a combination of custom hardware design and distributed event detection algorithms. We then continue to present a brief evaluation of the detection accuracy and the energy consumption that is achievable by current systems.
Cited by 38
Hongli Dong, Zidong Wang, Steven X. Ding et al. · 2016
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In recent years, theoretical and practical research on large-scale networked systems has gained an increasing attention frommultiple disciplines including engineering, computer science, and mathematics. Lying in the core part of the area are the distributed estimation and fault detection problems that have recently been attracting growing research interests. In particular, an urgent need has arisen to understand the effects of distributed information structures on filtering and fault detection in sensor networks. In this paper, a bibliographical review is provided on distributed filtering and fault detection problems over sensor networks. The algorithms employed to study the distributed filtering and detection problems are categorised and then discussed. In addition, some recent advances on distributed detection problems for faulty sensors and fault events are also summarized in great detail. Finally, we conclude the paper by outlining future research challenges for distributed filtering and fault detection for sensor networks. 1.
Cited by 0
Anang Hudaya Muhamad Amin, Asad I. Khan, Raja Azlina Raja Mahmood · 2009
Many of the existing event detection schemes in wireless sensor networks that employ classification or clustering approaches suffer from high communication and computational overheads. We propose a low-computation, distributed, and lightweight event detection scheme in wireless sensor networks, which is adopted from the pattern recognition scheme known as Distributed Hierarchical Graph Neuron. The experimental results show that the proposed scheme guarantees satisfactory classification accuracy, in comparison to Support Vector Machine and Self-Organizing Map algorithms.
Cited by 1
Bo Chen, Masayoshi Tomizuka · 2008
Wireless sensor networks have been receiving an increasing interest in the field of structural health monitoring to provide rich sets of real-time information of complex structures. Due to the bandwidth and power limitation of wireless sensor networks, distributed data processing, damage detection, and decision making are appropriate for the development of wireless structural health monitoring systems, which requires wireless sensor units equipped with data processing and damaged detection algorithms. This paper proposes an open software architecture design approach for the implementation of structural health monitoring algorithms in wireless sensor nodes. The open software architecture design approach promotes software reuse and welcomes the contributions from research communities.
Cited by 10
L. J. Dowell, Matteo Bruno · University of North Texas Digital Library (University of North Texas) · 2000
Distributed sensor networks are systems of sensor nodes interconnected by communication networks.The networks support advanced detection algorithms that use distributed computing to detect events as emergent phenomena of the system of sensors.These systems depend on connected and reliable communication networks.The systems are characterized typically by random nodal distribution and are directly related to mobile peer-to-peer networks having similar characteristics and problems.This paper explores models of these networks based on techniques of analyses of random graphs.Through evaluation of areas within the communication network uncovered by nodes, a model for connectivity of networks is developed.
Cited by 0Open access
Norman Dziengel, Georg Wittenburg, Jochen Schiller · 2008
Abstract—Distributed event detection in wireless sensor networks (WSNs) is the process of observing and evaluating an event using multiple sensor nodes without the help of a base station or other means of central coordination and processing. Current approaches to event detection in WSNs transmit raw data to an external entity for evaluation or rely on simplistic pattern recognition schemes. This implies either high communication overhead or low event detection accuracy, especially for complex events. In this paper, we present our currently on-going work on a system for distributed event detection that particularly suits the specific characteristics of WSNs. Adapting traditional pattern recognition algorithms to highly embedded devices, it uses the distributed sampling of sensor nodes to optimize the accuracy of the event detection process. Four different algorithms for distributing, classifying and fusing “fingerprints ” of the raw data sampled on each sensor are proposed and quantitatively evaluated in a small-scale experiment.
Cited by 0
Gernot Fabeck, Daniel Bielefeld, Rudolf Mathar · 2008
Cross-layer design for wireless networks aims at optimizing system-wide performance measures by exploiting dependencies between different network layers. In this paper, an opportunistic power assignment algorithms for IR-UWB sensor networks is presented that is especially designed for distributed signal detection under resource constraints. Specifically, the objective is to minimize the global probability of error of distributed detection systems, given a fixed level of total transmission power. The cross-layer approach for the allocation of transmission power is based on individual sensor detection quality as well as location information. It leads to significant performance gains compared to uniform power assignment for both the parallel and the serial sensor network topology.
Cited by 3
John R. Delaney, Richard T. Lacoss, P. E. Green · 1983
The acoustic tracking algorithms currently used in the MIT Lincoln Laboratory distributed sensor networks (DSN) testbed is described. The original motivation for inclusion of various features in those algorithms and the lesson learned about those features through experimentation with real and simulated data are discussed. Plans for modifications to the detection and tracking algorithms are sketched.
Cited by 5
Vatsalya Kunchakarra · 2005
Wireless sensor networks, a distributed network of sensor nodes perform critical tasks in many application areas such as target tracking in military applications, detection of catastrophic events, environment monitoring, health applications etc. The routing protocols developed for these distributed sensor networks need to be energy efficient and scalable. To create a better understanding of the performance of various routing protocols proposed it is very important to perform a detailed analysis of them. Network simulators enable us to study the performance and behavior of these protocols on various network topologies. Many Sensor Network frameworks were developed to explore both the networking issues and the distributed computing aspects of wireless sensor networks. The current work of simulation study of routing protocols is done on SensorSimulator, a discrete event simulation framework developed at Sensor Networks Research Laboratory, LSU and on a popular event driven network simulator ns2 developed at UC Berkeley. SensorSimulator is a discrete event simulation framework for sensor networks built over OMNeT++ (Objective Modular Network Test-bed in C++). This framework allows the user to debug and test software for distributed sensor networks. SensorSimulator allows developers and researchers in the area of Sensor Networks to investigate topological, phenomenological, networking, robustness and scaling issues, to explore arbitrary algorithms for distributed sensors, and to defeat those algorithms through simulated failure. The framework has modules for all the layers of a Sensor Network Protocol stack. This thesis is focused on the simulation and performance evaluation of various routing protocols on SensorSimulator and ns2. The performance of the simulator is validated with a comparative study of Directed Diffusion Routing Protocol on both ns2 and SensorSimulator. Then the simulations are done to evaluate the performance of Optimized Broadcast Protocols for Sensor Networks, Efficient Coordination Protocol for Wireless Sensor Networks on SensorSimulator. Also a performance study of Random Asynchronous Wakeup protocol for Sensor Networks is done on ns2.
Cited by 2Open access
Arindam Das, Mehran Mesbahi · IEEE Transactions on Aerospace and Electronic Systems · 2009
In this paper, we consider distributed linear least squares (LLS) and Bayesian minimum mean square error (BMMSE) parameter estimation over sensor networks. In particular, we propose distributed iterative algorithms that asymptotically converge to the centralized solutions. These algorithms are first studied for the case of unclustered (flat architecture) sensor networks; in this venue, we provide necessary and sufficient conditions for the distributed algorithm to converge. Subsequently, we extend our analysis to clustered sensor networks with pulsed inter-cluster updates. In this latter scenario, inter-cluster communications occur every ß time steps (with ß > 1) and the corresponding updates are held until the next update instant. Depending on sensor locations and the employed network topology construction algorithm, it may be the case that inter-cluster communications require higher transmitter power support than intracluster communications. For energy-constrained sensor networks, it will therefore be beneficial-from a power efficiency (or alternately, network lifetime) point of view-to limit the extent of inter-cluster communication, without significantly deteriorating the convergence properties of the distributed estimation algorithm. We anticipate that a pulsed inter-cluster update scheme will also be useful for applications such as ground or airborne sensor networks, where low probability of detection and interception is essential. Our analysis provides sufficient conditions under which such distributed estimation algorithms, operating on a pulsed inter-cluster update scheme, converge. Simulation results illustrating the dependence of the convergence rate of the algorithm on the hold interval ß conclude the paper.
Cited by 23
2014
Efficiency improvement in multi-sensor wireless network based estimation algorithms for distributed parameter systems with application at the heat transfer Constantin Volosencu * and Daniel-Ioan Curiac This paper gives a technical solution to improve the efficiency in multi-sensor wireless network based estimation for distributed parameter systems. A complex structure based on some estimation algorithms, with regression and autoregression, implemented using linear estimators, neural estimators and ANFIS estimators, is developed for this purpose. The three kinds of estimators are working with precision on different parts of the phenomenon characteristic. A comparative study of three methods- linear and nonlinear based on neural networks and adaptive neuro-fuzzy inference system- to implement these algorithms is made. The intelligent wireless sensor networks are taken in consideration as an efficient tool for measurement, data acquisition and communication. They are seen as a “distributed sensor”, placed in the desired positions in the measuring field. The algorithms are based on regression using values from adjacent and also on auto-regression using past values from the same sensor. A modelling and simulation for a case study is presented. The quality of estimation is validated using a quadratic criterion. A practical implementation is made using virtual instrumentation. Applications of this complex estimation system are in fault detection and diagnosis of distributed parameter systems and discovery of malicious nodes in wireless sensor networks.
Cited by 0
Mingfei Wang, Linlin Ci, Ping Zhang et al. · 2007
In recent years, wireless sensor networks have become an evolving technology that has a wide range of potential applications. Acoustic source localization is a hot research topic with many possible application areas, such as voice enhancement, intruder detection, sniper localization, and automatic tracking of speakers in an e-conferencing environment. Utilization of wireless sensor networks for acoustic source localization can provide good coverage, which not only enhances the accuracy, but also increases the robustness of the overall system. In this paper, we gave an overview of the acoustic source localization based on wireless sensor networks. Firstly, we analyzed the characteristics of acoustic source localization in wireless sensor networks. Then, we classified the existing typical acoustic source localization alogrithms in wireless sensor networks into centralized alogrithms and distributed algorithms. At the same time, we introduced the algorithms and discussed both merits and drawbacks of the algorithms. Finally, we pointed out the design issues of related middleware services.
Cited by 4
Constantin Voloşencu, Daniel-Ioan Curiac · EURASIP Journal on Advances in Signal Processing · 2013
This paper gives a technical solution to improve the efficiency in multi-sensor wireless network based estimation for distributed parameter systems. A complex structure based on some estimation algorithms, with regression and autoregression, implemented using linear estimators, neural estimators and ANFIS estimators, is developed for this purpose. The three kinds of estimators are working with precision on different parts of the phenomenon characteristic. A comparative study of three methods -linear and nonlinear based on neural networks and adaptive neuro-fuzzy inference system -to implement these algorithms is made. The intelligent wireless sensor networks are taken in consideration as an efficient tool for measurement, data acquisition and communication. They are seen as a "distributed sensor", placed in the desired positions in the measuring field. The algorithms are based on regression using values from adjacent and also on auto-regression using past values from the same sensor. A modelling and simulation for a case study is presented. The quality of estimation is validated using a quadratic criterion. A practical implementation is made using virtual instrumentation. Applications of this complex estimation system are in fault detection and diagnosis of distributed parameter systems and discovery of malicious nodes in wireless sensor networks.
Cited by 9Open access
Lang Tong · 2009
Abstract : This project investigates distributed signal processing in the context of sensor enhanced mobile ad hoc networks. The objective of the project is twofold. First, the research aims to create a new framework for Network Centric Signal Processing that facilitates a joint design of communications, networking, and signal processing optimized for specific applications. Second, for sensor networks deployed for detection and estimation, this research develops new multiaccess communication strategies, networking protocols (medium access control and routing), and centralized and decentralized signal detection and estimation algorithms.
Cited by 0