An algorithm of mobile sensors data fusion tracking for. Keywords wsn, data aggregation, data fusion, sensor network, iot i. A strategy for avoiding energy holes based on data fusion in wireless sensor network p. Data fusion in wireless sensor networks yun liu, qingan.
In conventional systems, raw or traditionally preprocessed sensor measurements reach the application directly, which has to deal with imprecise, ambiguous and incomplete data streams. Information fusion for wireless sensor networks ucf. Pdf systemlevel calibration for data fusion in wireless. 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. When a sensor node sends out a packet, it puts the residual energy e r in the header file of the data packet to convey the information to the. Introduction a wireless sensor network is a network which comprises. China xue liu, mcgill university, canada jianguo yao, shanghai jiao tong university, p. A method to reduce energy consumption and, as a result, increase the network lifetime is the fusion of data collected from the sensors in the covered environment before transmission to wireless sensor network. Wsn nodes have less power, computation and communication compared to manet nodes.
In this paper, optimization of network is formulated by cuckoo based particle approach cbpa. A new data fusion algorithm for wireless sensor networks. Need for energy efficient data fusion in wireless sensor networks jayasri b. Design and optimization of distributed sensing coverage in. 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. Data fusion improves the coverage of wireless sensor. Pdf data fusion in wireless sensor networks biljana. A further motivation for sensor fusion is the reduction of application logic complexity. Nakamura analysis, research and technological innovation center fucapi federal university of minas gerais ufmg antonio a. The design of largescale sensor networks interconnecting various sensor nodes has spurred a great deal of interest due to its wide variety of applications.
The aim of this thesis is to develop data fusion strategies for wireless sensor networks wsn that remove temporal or spatial redundancies between sensor measurements in order to decrease the. Extending lifetime of wireless sensor networks using multi. The purpose of the network is to sense the environment and report what happens in the area it is deployed in. Simulation and research on data fusion algorithm of the wireless sensor network based on ns2 3. To solve this problem, we proposed a phased array image method based on compressive sampling and data fusion for wireless structural damage monitoring. Fellow, ieee abstractwe propose a distributed sequential estimation scheme for wireless sensor networks with asynchronous measurements.
This is especially problematic in data fusion, where a small fraction of low quality. Sensor data fusion in the internet of things arxiv. In experiments, smart wireless sensors, and a digital camera are used. 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. Wireless sensor networks may be considered a subset of mobile adhoc networks manet. 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 managing. Energyefficient data fusion technique and applications in wireless sensor networks. 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. Scalable structurefree data fusion on wireless sensor networks 5107 fig. Data fusion techniques for auto calibration in wireless sensor networks maen takruri 1, subhash challa 2, ramah yunis 1 centre for realtime information networks crin university of technology, sydney, australia 2 nicta victoria research laboratory, australia email.
Data fusion, which fuses the collected data before they are sent to the base station, is usually. 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. Data fusion utilization for optimizing largescale wireless sensor networks mohammadreza soltani, michael hempel, hamid sharif advanced telecommunications engineering laboratory, dept. Data fusion and collaborative state estimation in wireless sensor. Low complexity indoor localization in wireless sensor.
Due to the limitations of sensor nodes capabilities, especially the strictly limited energy, innetwork data processing, such as data fusion which can significantly improve the. 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. 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. Pdf data fusion techniques in wireless sensor networks. Pdf on jun 1, 2018, mahnaz koupaee and others published data fusion techniques in wireless sensor networks. Introduction recent years have witnessed the deployments of wireless sensor networks wsns for many critical applications such as security surveillance 16, environmental monitoring 25, and target detectiontracking 21. Scalable structurefree data fusion on wireless sensor. This paper highlights the advantages of data fusion and topology control in wireless sensor networks. Data fusion techniques reduce total network traffic in a wireless sensor network, since data fusion can integrate multiple raw data sets into one fused data set. Han,member, ieee abstract wireless sensor networks place sensors into an area to collect data and send them back to a base station. Loureiro federal university of minas gerais ufmg and alejandro c. Industriale e dellinformazione via ferrata 1 27100 pavia, italy email.
Due to the limitations of some sensor nodes, especially the limited amount of energy, in network data processing, such as data fusion, is very important. Journalofsensors energyefficient data fusion technique and applications in wireless sensor networks. Fusion of stereo depth maps and sensor localization in. An approach to implement data fusion techniques in wireless.
Wireless sensor data fusion for critical infrastructure security. Research article secure data fusion in wireless multimedia. Wireless sensor data fusion for critical infrastructure security francesco flammini 1 2, andrea gaglione 2, nicola mazzocca 2, vincenzo moscato 2, concetta pragliola 1 1 ansaldo sts ansaldo segnalamento ferroviario s. 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. On the other hand, serial data fusion imposes the utilization of routing algorithms. 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. This paper focuses on the challenges involved in supporting fusion applications in wireless ad hoc sensor networks wasn. Clustering based data collection using data fusion in.
It is an open source and free software simulation platform which aims at network technology. Systemlevel calibration for data fusion in wireless sensor. Tripathi department of computer science and engineering, university of california, riverside, riverside, ca, 92521 abstractin wireless sensor networks, innetwork data fusion. The wsn is built with nodes that are used to observe the surroundings like temperature, humidity, pressure, position, vibration, sound etc. The paper provides a more detailed look at some existing data fusion and topology management algorithms. Fuzzy data fusion for fault detection in wireless sensor. Our aim is to provide a better understanding of the current research issues in this field.
Alexandre ciancio, sundeep pattem, antonio ortega, bhaskar krishnamachari, energyefficient data representation and routing for wireless sensor networks based on a distributed wavelet compression algorithm, proceedings of the 5th international conference on information processing in sensor networks, april 1921, 2006, nashville, tennessee. 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. Synchronization of multiple levels of data fusion in wireless sensor networks wei yuan, srikanth v. A witnessbased approach for data fusion assurance in wireless sensor networks wenliang du,jingdeng, yunghsiang s. A wsn consists of many sensor nodes that cooperate with each other to perform a measurement or monitoring task, in which data are exchanged and shared between neighbours through wireless communication. Pdf study of data fusion in wireless sensor network. Contemporary energy efficient optimization schemes are focused on reducing power consumption in various aspects of hardware design, data processing, network protocols and operating system. Data fusion in wireless sensor networks ieee conference. Distributed wireless sensor networks is a collection of embedded sensor devices with networking capabilities.
Pdf the success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding. Santhi assistant professor, dept of cse, annamalai university, annamalainagar, india r. Fuzzy data fusion for fault detection in wireless sensor networks. Compressive sampling and data fusionbased structural damage. Zhai et al 4 proposed an algorithm space wireless sensor networks for planetary exploration swipe, where two types of data are processed separately in the data fusion module. Data fusion and topology control in wireless sensor networks. Due to the advantage of data fusion in deleting redundant information and extending lifetime of network, data fusion has become one of the important ways of effectively relieving the bottleneck of wireless sensor networks resources, which has been widely used in wireless sensor networks. In addition, the gating technique is also applied to solve the problem of msdft mobile sensor data fusion tracking for targets, i. In addition, the gating technique is also applied to solve the problem of msdft mobilesensor data fusion tracking for targets, i. Data fusion and collaborative state estimation in wireless sensor networks. Research on the wireless sensor network data fusion. In this edited reference, the authors provide advanced tools for the design, analysis and.
Wireless sensor networks wsns are resourceconstrained networks, especially when the energy is highly constrained. First, compressive sampling signal by compressive sampling method was collected. A data fusion method in wireless sensor networks ncbi. A strategy for avoiding energy holes based on data fusion in. Event detection services using data service middleware in. Data fusion and collaborative state estimation in wireless. In this phd dissertation we study the problem of continuous object tracking using large.
Wireless sensor networks introduction to wireless sensor networks february 2012 a wireless sensor network is a selfconfiguring network of small sensor nodes communicating among themselves using radio signals, and deployed in quantity to sense, monitor and understand the physical world. Systemlevel calibration for data fusion in wireless sensor networks rui tan, michigan state university, usa guoliang xing, michigan state university, usa zhaohui yuan, huadong jiao tong university, p. Synchronization of multiple levels of data fusion in wireless. Distributed signal processing and data fusion methods for large scale wireless sensor network applications dimitris v. 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.
Systemlevel calibration for data fusion in wireless. A novel approach to improving three dimensional scene geometry and sensor locations by fusing localization data from wireless sensor networks wsn with depth maps obtained through stereopsis is presented along with a software prototype. 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. Therefore, to maximize the lifetime of sensor networks, aggressive energy optimization techniques have to be used for ensuring that energy is conserved for the sensor nodes. Research article secure data fusion in wireless multimedia sensor networks via compressed sensing ruigao, 1,2 yingyouwen, 1,2 andhongzhao 1,2 college of information science and engineering, northeastern university, shenyang, china. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering. Wireless sensor network wsn architecture and applications. Clustering based data collection using data fusion in wireless sensor networks s. Pdf a data fusion method in wireless sensor networks. Data fusion based on node trust evaluation in wireless sensor. Han abstract wireless sensor networks place sensors into an area to collect data and send them back to a base station. Reliable data fusion in wireless sensor networks under. Data fusion, in which collected data are fused before they are sent to the base station, is usually implemented over the network. Distributed sequential estimation in asynchronous wireless.
Data fusion techniques for auto calibration in wireless. Energyefficient data fusion technique and applications in wireless sensor networks guest editors. Wireless sensor networks wsns consist of a large number of source limited wireless sensor nodes for the purpose of data collection, processing, and transmission. Information fusion, data aggregation, data fusion, wireless sensor net. Research article an anomaly detection based on data fusion. 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. Data fusion in sensors is defined as the process 1. Energyefficient data fusion technique and applications in. Systemlevel calibration for data fusion in wireless sensor networks. In order to reduce the data processing load on bs and efficiently distinguish the authenticity of archived data, izadi et al. Numerous tiny sensors are restricted with energy for the wireless sensor networks since most of them are deployed in harsh environments, and. Fei j 2011 a data fusion strategy of wireless sensor networks based on specific applications. As an important element of internet of things, wireless sensor networks wsn are composed of many compact microsensors.
Data fusion in wireless sensor network can realize different protocol layers, based on the introduction of wireless sensor network and data fusion related knowledge. China wireless sensor networks are typically composed of lowcost sensors that are deeply integrated. Then, data fusion for multi sensor s damage response signal was implemented in phased array. Data fusion based on distributed quality estimation in. Data fusion and collaborative state estimation in wireless sensor networks hiba haj chhade to cite this version. Distributed sequential estimation in asynchronous wireless sensor networks ondrej hlinka, franz hlawatsch, fellow, ieee,andpetarm. Contemporary en ergy efficient optimization schemes are focused on reducing power consumption in various aspects of hard ware design, data processing, network protocols and operating system. Localisation of a mobile object in a wireless sensor network. Study on data fusion techniques in wireless sensor networks. In wireless sensor networks, using the data fusion at different. Data fusion in wireless sensor networks using fuzzy systems. Abstract wireless sensor networks consist of a large number sensor nodes that are deployed in some geographical area. Belief propagation algorithm, a wellknown data fusion algorithm that is widely used for.
These sensors detect the concentration of the emitted substance. The aim of the thesis is to develop fusion algorithms for data collected from a wireless sensor network in order to locate multiple sources emitting some chemical or biological agent in the air. Frery federal university of alagoas ufal wireless sensor networks produce a large amount of data that needs to be processed, delivered, and assessed according to the application objectives. This paper discusses about wireless sensor network, its architecture, data aggregation or fusion related algorithms. An intelligent data gathering schema with data fusion supported for. Pdf energy consumption in wireless sensor networks using. Varshney abstractin wireless sensor networks, sensor nodes are spread randomly over the coverage area to collect information of interest. The objective of a wsn is to utilize the data at different locations to enhance the measurement performance. In this paper, we have presented a fuzzybased method for data fusion.
In 15, a variable weightbased fuzzy data fusion algorithm is proposed. Data fusion improves the coverage of wireless sensor networks. Distributed signal processing and data fusion methods for. Multisensor data fusion research focuses on solutions that fuse data from multiple sensors to provide more accurate estimation of the environment 1622. Data fusion privacy preserving algorithm based on failure. Energy efficient communication is a plenary issue in wireless sensor networks wsns. A new data fusion algorithm for wireless sensor networks inspired. Data fusion in the internet of things sciencedirect. Sensor fusion is also known as multi sensor data fusion and is a subset of information fusion. Simulation and research on data fusion algorithm of the. We also explain each of the parameters in much more detail lines 434481. A study on data fusion of wireless sensor networks security. Due to the limitations of sensor nodes capabilities, especially the strictly limited energy, in network data processing, such as data fusion which can significantly improve the.
Data fusion in wireless sensor networks hungta pai, member, ieee, and yunghsiang s. A arietvy of factors such as sensor failure or data loss in communication may cause a wsn to produce incorrect data. In this paper, we present a fuzzybased data fusion approach for wsn with the aim of increasing the qos whilst reducing the energy consumption of the sensor network. Abstract wireless sensor networks consist of large number. The success of a wireless sensor network wsn deployment strongly depends on the quality of service qos it provides regarding issues.
Reliable data fusion in wireless sensor networks under byzantine attacks mai abdelhakim leonard e. In network data aggregation and fusion see jones, sivalingam, agrawal, and chen survey article in acm winet, july 2001. Currently, wsn wireless sensor network is the most standard services employed in commercial and industrial applications, because of its technical development in a processor, communication, and lowpower usage of embedded computing devices. As the communication consumes a significant part of the energy in wireless networks, ordinary parallel data fusion approaches may expend more energy than serial data fusion techniques, due to the fact that all sensed data is sent to a central node.
Data fusion, target detection, coverage, performance limits, wireless sensor network 1. Unfortunately, low data quality is a prevalent problem in wsns. Manets have high degree of mobility, while sensor networks are mostly stationary. A witnessbased approach for data fusion assurance in. Ns2 introduction ns2 network simulator version2 was developed by ucberkeley in united states. While innetwork data fusion can reduce data redundancy and hence curtail network load, the fusion process itself may introduce signi. Wireless sensor networks produce a large amount of data that needs to be. Energy efficient computation of data fusion in wireless. Compressive sampling and data fusionbased structural. However, the security or assurance of the data requires more processing power and is an.
When a sensor node sends out a packet, it puts the residual energy e r in the header file of the data packet to convey the information to the neighbor nodes. Then, data fusion for multisensors damage response signal was implemented in phased array. Data fusion is a critical step in designing a wireless sensor network as it handles data acquired by sensory devices. In mobileagentbased data fusion approaches, software that aggregates sensor information are packed and dispatched as mobile agents to hot areas e. In this research study, an energy efficient cluster head selection in mobile wireless sensor networks is proposed, analysed and validated on the basis of residual energy and randomized selection. Need for energy efficient data fusion in wireless sensor.
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