It is an open source and free software simulation platform which aims at network technology. Data fusion can effectively reduce the volume of data transmission in the network, reduce the energy consumption to extend network lifetime and improve bandwidth utilization, as a result, it can overcome the restriction. Manets have high degree of mobility, while sensor networks are mostly stationary. Direct fusion is the fusion of sensor data from a set of heterogeneous or homogeneous sensors, soft sensors, and history values of sensor data, while indirect fusion uses information sources like a priori knowledge about the environment and human input. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and spatial and temporal coverage problems. An intelligent data gathering schema with data fusion. Data fusion can effectively reduce the amount of data transmission and network energy consumption in wireless sensor networks wsns. Wireless sensor networks may be considered a subset of mobile adhoc networks manet. This book constitutes the refereed proceedings of the 11th china conference on wireless sensor networks, cwsn 2017, held in tianjin, china, in october 2017. Developing a fusion application is challenging in general, for the fusion operation typically requires timecorrelation and synchronization of data streams coming from several distributed sources. Data fusion is a research area that is growing rapidly due to the fact that it provides means for combining pieces of information coming from different sourcessensors, resulting in ameliorated overall system performance improved decision making, increased detection capabilities, diminished number of false alarms, improved reliability in various situations at hand with respect to separate. On the other hand, data fusion can effectively decrease data redundancy, reduce the amount of data transmission and.
Intelligent data fusion algorithm based on hybrid delay. The journal is intended to present within a single forum all of the developments in the field of multi sensor, multisource, multiprocess information fusion and thereby promote the synergism among the many disciplines that are contributing to its growth. Data fusion approach for error correction in wireless sensor. A statistical signal processing perspective, published by the institute of. Sensor fusion is also known as multi sensor data fusion and is a subset of information fusion. Sensor systems covers sensors and multiple sensor systems, including sensor networks and multi sensor data fusion.
The role of data fusion has been expanding in recent years through the incorporation of pervasive applications, where the physical infrastructure is coupled with information and communication technologies, such as wireless sensor networks for the internet of things iot, ehealth and industry 4. Resourceaware data fusion algorithms for wireless sensor networks ebook written by ahmed abdelgawad, magdy bayoumi. Novel features of the text, distributed throughout, include workable solutions, demonstration systems and case studies of the design and application of wireless sensor networks wsns based on the firsthand research and development experience of the author, and the chapters on real applications. Data fusion in wireless sensor networks ieee conference. The use of mobile agents for data fusion in wireless sensor networks has been recently proposed in the literature to answer the scalability problem of clientserver model. Resourceaware data fusion algorithms for wireless sensor networks lecture notes in electrical engineering. A statistical signal processing perspective control, robotics and sensors book online at best prices. Wireless positioning technologies and applications gnss. Emerging machine learning technology provides a novel direction for data fusion and makes it more available and intelligent.
Ns2 introduction ns2 network simulator version2 was developed by ucberkeley in united states. Pdf study of data fusion in wireless sensor network. Data fusion in wireless sensor networks a statistical signal processing. Therefore, energy consumption in wireless sensor networks is one of the most challenging problems in practice. When having a look at wireless sensor networks, a huge number of tiny devices equipped with lowcost radio transceivers form a selforganizing ad hoc network. Impact of data fusion on realtime detection in sensor networks rui tan 1guoliang xing2 benyuan liu3 jianping wang 1city university of hong kong, hksar 2michigan state university, usa 3university of massachusetts lowell, usa abstractrealtime detection is an important requirement of many missioncritical wireless sensor network applications. A data fusion method in wireless sensor networks article pdf available in sensors 152. The iet shop data fusion in wireless sensor networks. Data fusion in the internet of things sciencedirect. Wireless sensor nodes are batterypowered devices with limited processing and. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering.
Energyefficient and reliable transmission of sensory information is a key problem in wireless sensor networks. To resolve the above problems, an energyefficient sleep scheduling mechanism with similarity measure for wireless sensor networks essm is proposed, which will schedule the sensors into the active or sleep mode to reduce energy consumption. This chapter focuses on a cognitive wireless sensor network wsn, where a primary wireless sensor network pwsn is colocated with a cognitive sensor network. Data fusion with desired reliability in wireless sensor networks abstract. Efficient data fusion for wireless sensor networks. Mar 25, 2019 a wireless sensor network consists of sensor nodes we will see about this later that are deployed in high density and often in large quantities and support sensing, data processing, embedded computing and connectivity. Offers a practical applicationsoriented approach to solving sensor network issues. In 15, a variable weightbased fuzzy data fusion algorithm is proposed. This is especially challenging in data fusion mechanisms, where a small fraction of low quality data in the fusion input may negatively impact the overall fusion. This paper gives a survey on classical data fusion in wireless sensor networks from the following aspects. Low complexity indoor localization in wireless sensor networks by uwb and inertial data fusion alberto savioli, emanuele goldoni, pietro savazzi, and paolo gamba university of pavia dipartimento di ing. The effective use of data fusion in sensor networks is not new and has had extensive application to surveillance, security, traffic control, health care, environmental and industrial monitoring in the last decades. As an important element of internet of things, wireless sensor networks wsn are composed of many compact microsensors.
This article introduces a timeselective strategy for enhancing temporal consistency of input data for multi sensor data fusion for in network data processing in ad hoc wireless sensor networks. The data fusion process occurs within the sensor network rather than at a. Abstract wireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area. Whether youve loved the book or not, if you give your honest and detailed thoughts then people will find new books that are right for them. Basics of wireless sensor networks wsn classification.
Data fusion with desired reliability in wireless sensor. Simulation and research on data fusion algorithm of the wireless sensor network based on ns2 3. The main aspects of these types of systems are wireless sensor networks wsn, cloud and communication networks. It presents the physics and principles of operation and discusses sensor selection, ratings and performance specifications, necessary hardware and software for integration into an engineering system, and signal processing and data analysis. In order to improve the efficiency of data fusion in wireless sensor networks and reduce the energy consumption of the system, a new method of data fusion based on gso algorithm for optimizing bp neural network is proposed. Following the latest developments in computer and communication technologies, everyday objects are becoming smarter, as ubiquitous connectivity and modern sensors allow them to communicate with each other. This book describes the advanced tools required to design stateoftheart inference algorithms for inference in wireless sensor networks. Data aggregation is necessary for wireless sensor networks. An energyefficient sleep scheduling mechanism with. A delayaware network structure for wireless sensor networks with in network data fusion abstract. In idgsdf, we adopt a neural network to conduct data fusion to improve network performance.
Wireless sensor network wsn refers to a group of spatially dispersed and dedicated sensors. A statistical signal processing perspective, published by the institute of engineering and technology iet, apr. With recursive least square method in the algorithm, the dynamic model of sensor was built up, and the achievement of data fusion between sensor s measure value and estimate value increased the measure precision. Multiorder fusion data privacypreserving scheme for wireless. Pdf multisensor data fusion in wireless sensor networks for. One of the most important challenges of such networks is the distributed management of the huge amount of data produced by sensors in network to reduce data traffic in network and minimize the energy. Handling sensing data errors and uncertainties in wsn while maximizing network lifetime are important issues in the design of applications and protocols for wireless sensor networks. Minimizing network traffic and consequently overall energy consumption, scalability, etc. Wireless sensor and actuator networks sciencedirect. Lee resourceaware data fusion algorithms for wireless sensor networks por ahmed abdelgawad disponible en rakuten kobo.
Part iii is on data storage and manipulation in sensor networks, and part iv deals with security protocols and mechanisms for wireless sensor networks. From algorithms and architectural design to applications. Resourceaware data fusion algorithms for wireless sensor networks lecture notes in electrical engineering abdelgawad, ahmed, bayoumi, magdy on. The term data aggregation has become popular in the wireless sensor network com munity as a synonym for information fusion kalpakis et al. A data fusion method in wireless sensor networks mdpi. Impact of data fusion on realtime detection in sensor networks. This paper is compared with two algorithms, namely a data fusion method in wireless sensor networks dfm and data fusion in wireless sensor networks using fuzzy set theory dffst. A multisensor data fusion technique using data correlations.
Wireless sensor networks wsns are resourceconstrained networks, especially when the energy is highly constrained. Data fusion in wireless sensor networks yun liu, qingan. Resourceaware data fusion algorithms for wireless sensor networks. The journal is the premier vehicle for disseminating. Wireless sensor network data fusion based on gso improved bp. However the existing data fusion schemes lead to additional delay overhead and power consumptions. Expert guidance on integrating wifi, wimax, and zigbee into seamless wireless networks the latest methods for ensuring security across the wireless network in depth coverage of data fusion principles vital information on smartmesh networking in sensornets autonomic selfware and bioinspired communication. Surveillance tracking systems, disaster management, medical systems, transportation, business intelligence, environmental monitoring systems, elearning and virtual campuses, smart grids and energy efficiency systems, etc. Download for offline reading, highlight, bookmark or take notes while you read resourceaware data fusion algorithms for wireless sensor networks. In a centralized situation, data are forwarded to a central location to be correlated and fused. The wireless sensor network wsn is mainly composed of a large number of sensor nodes that are equipped with limited energy and resources. For the sake of avoiding the data abundance and balancing the energy consumption in wireless sensor networks, a data fusion clustering hierarchy based on data fusion chdf is proposed.
Advanced techniques have been introduced, including data aggregation or data fusion. Introduces the latest technology in wireless sensor networks, networked embedded systems and their applications. Pdf systemlevel calibration for data fusion in wireless. Decision fusion in cognitive wireless sensor networks. The proposed algorithm can greatly increase the safety and accuracy of data fusion, improve communication efficiency, save energy of sensor node, suit different application fields, and deploy environments. Varshney, geographic routing in wireless ad hoc networks, book chapter, guide to wireless. In proceedings of the 4th international conference on networking icn 2005, p. The book is directed at the sensing, signal processing, and icts research.
In this paper, we have presented a fuzzybased method for data fusion. Pdf the swipe space wireless sensor networks for planetary exploration project uses wireless sensor networks wsn to characterise. In typical wireless sensor networks, sensor nodes are usually limited in resources and energy. Energy management in wireless sensor networks discusses this unavoidable issue in the application of wireless sensor networks wsn. Scalable structurefree data fusion on wireless sensor networks. Wireless sensor networks are used to monitor wine production, both in the field and the cellar. In this paper we present an index table management to manage the receiving buffer for improving packets merging. In wireless sensor networks, there are large numbers of packets in the receiving buffer of sink node. Data fusion can effectively reduce the volume of data transmission in the network, reduce the energy consumption to extend network lifetime and improve bandwidth utilization, as a result. A new data fusion algorithm for wireless sensor networks inspired. The reason for choosing these two algorithms is that both choose fuzzy theory in the data fusion of a wireless sensor network, and they carry out forest fire prediction analysis, which is very similar to our algorithm. Based on the management pattern of cluster structure, in 1, conti et al. Wireless sensor network news newspapers books scholar jstor may 2011 learn how and when to remove this template message. Simulation and research on data fusion algorithm of the.
This edition includes updated and expanded chapters on satellite navigation, ofdm orthogonal frequency division multiplex, tdoa location facilities in 3gpp lte specifications, carrier phase measurements and dgps, wireless sensor networks, mimo positions, inertial navigation, and data fusion. In addition, the gating technique is also applied to solve the problem of msdft mobilesensor data fusion tracking for targets, i. Data fusion in wireless sensor networks wsns can improve the performance of a network by eliminating redundancy and power consumption, ensuring faulttolerance between sensors, and. Wireless sensor networks presents the latest practical solutions to the design issues presented in wireless sensor networkbased systems. Salvo rossi, data fusion in wireless sensor network. Wireless sensor networks presents a comprehensive and tightly organized compilation of chapters that surveys many of the exciting research developments taking place in this field. A delayaware network structure for wireless sensor. Data fusion and topology control in wireless sensor networks. A survey on routing protocols for wireless sensor networks by abbas mohammed and zhe yang we are intechopen, the worlds leading publisher of open access books.
The recent developments in engineering, communication and networking has led to new. Data fusion based on node trust evaluation in wireless sensor. To save more energy, in network processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes in the data fusion tree. In addition to networking, data management is an important challenge given the high volumes of data that are generated by sensor nodes. The application prospect in the market with huge thing networking are buzzing the third wave of information technology, its one of the core technology on two wireless sensor networks with energy, storage capacity, computing power, communications bandwidth resource constraints of the salient characteristics of data fusion, implementation is the inevitable choice. The distinguishing aspect of our work is the novel use of fuzzy membership functions and rules in the design of cost functions for the routing objectives considered in this work. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. This chapter deals with a wireless sensor and actuator network wsan and its main characteristics.
In order to reduce the data processing load on bs and efficiently distinguish the authenticity of archived data, izadi et al. The data which needs to be disseminated from multiple sources to the destination base station, or sink, is of vital significance. An algorithm of mobile sensors data fusion tracking for. A wireless sensor network wsn comprises a large number of wireless sensor nodes. Wireless sensor networks and data fusion techniques data analytics applications. To guarantee efficiency and durability in a network, the science must go beyond hardware solutions and seek alternative software solutions that allow for better data control from the source to delivery. While wireless sensor networks wsns have been traditionally tasked with single applications, in recent years we have witnessed the emergence of wsns that allow the sensing and communication infrastructure to be shared among multiple applications thus optimizing the use of resources. Pdf a data fusion method in wireless sensor networks. Decisionlevel fusion takes information from each sensor after it has measured or evaluated a target individually. Varshney, multiobjective evolutionary algorithms for wireless sensor network design, multiobjective optimization in computational intelligence. In this article, we present an intelligent data gathering schema with data fusion called idgsdf. Low complexity indoor localization in wireless sensor. In this paper an algorithm of data fusion to track both of nonmaneuvering and maneuvering targets with mobile sensors deployed in an wsn wireless sensor network is proposed and investigated. Wsn nodes have less power, computation and communication compared to manet nodes.
Data fusion algorithms for wireless sensor networks based. Data fusion in wireless sensor networks a statistical. Novel features of the text, distributed throughout, include workable solutions, demonstration systems and case studies of the design and application of wireless. Data fusion in wireless sensor networks maen takruri submitted in partial fulfillment of the requirements for the degree of doctor of philosophy faculty of engineering and inforrnation technology university of technology, sydney march 2009. Jun 21, 2018 in wireless sensor networks, the high density of nodes distribution will result in transmission collision and energy dissipation of redundant data. This paper focuses on the challenges involved in supporting fusion applications in wireless ad hoc sensor networks wasn. Read resourceaware data fusion algorithms for wireless sensor networks by ahmed abdelgawad available from rakuten kobo. To save more energy, innetwork processing such as data fusion is a widely used technique, which, however, may often lead to unbalanced information among nodes in the data fusion tree. Systemlevel calibration for data fusion in wireless sensor networks.
Written for the signal processing, communications, sensors and information fusion research communities, it covers the emerging area of data fusion in wireless sensor networks. May 16, 2017 recent advancements in sensor technology, wireless networks and consequently wireless sensor networks and the increase in their applications in different fields have led to their great importance. Data fusion with desired reliability in wireless sensor networks. A wireless sensor network wsn in its simplest form can be defined as a network of devices denoted as nodesthat can sense the environment and communicate the information gathered from the monitored field through wireless links.
A well designed buffer management could provide efficient packet merging so that it can reduce the number of packets and the transmission overhead. Data fusion algorithms of single sensor in wireless sensor. The success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding issues such as data accuracy, data aggregation delays and network lifetime maximisation. Describes how to design and build wireless sensor networks. The algorithms described in this book are evaluated with simulation and experimental. Industriale e dellinformazione via ferrata 1 27100 pavia, italy email. Resourceaware data fusion algorithms for wireless sensor. Sensor fusion also can be centralized or decentralized depending on where the fusion of the data occurs. These techniques can be used in centralized and distributed systems to overcome sensor failure, technological limitation, and. Multi sensor was needed while using data fusion technique in wireless sensor networks. Information fusion for data dissemination in selforganizing wireless sensor networks. A data fusion algorithm of single sensor was proposed in the paper. In this article, we consider the problem of calculating a nearoptimal route.