Reliable data fusion in wireless sensor networks under byzantine attacks mai abdelhakim leonard e. Multisensor data fusion algorithm of triangle module. 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. In this article, we present an intelligent data gathering schema with data fusion called idgsdf. Tripathi department of computer science and engineering, university of california, riverside, riverside, ca, 92521 abstractin wireless sensor networks, in network data fusion. Data fusion in wireless sensor networks yun liu, qingan. In this paper, the data fusion process of mobile heterogeneous wireless sensor networks is mainly studied, and regards the nodes of wireless sensor. In the first phase, we used a network simulation where mobile agents dynamically select the next hop migration node based on the stability parameter of the link, and perform the. Data fusion, target detection, coverage, performance limits, wireless sensor network 1. Decisionmaking and fusion for mobile wireless sensor networks. An enhanced pegasis algorithm with mobile sink support for wireless sensor networks.
Mobile agent based data fusion for wireless sensor. In idgsdf, we adopt a neural network to conduct data fusion to improve network performance. Cbpa is listed in the worlds largest and most authoritative dictionary database of abbreviations and acronyms. In that case, data fusion in mobile wireless sensor networks mwsns will suffer from network delays, high and uneven energy consumption. Another approach to utilize a mobile data collector is presented in 26. In this paradigm, ma migrates among sensor nodes sns for data fusion. For the applications of the wsns most widely use numerical data, multi sensor data fusion tmmdf algorithm is designed in this paper. Quality estimation based data fusion in wireless sensor. Pdf a data fusion method in wireless sensor networks. Mobile agent itinerary planning for wsn data fusion. We consider the qoutofm rule, which is popular in distributed detection and can achieve a good tradeoff between the miss detection probability and the false alarm rate. This paper presents a wireless sensor network wsn system which was created as.
Information extraction ie is a key research area within the field of wireless sensor networks wsns. Multisensor data fusion in distributed sensor networks. This book constitutes the refereed proceedings of the 11th china conference on wireless sensor networks, cwsn 2017, held in tianjin, china, in october 2017. On computing multiagent itinerary planning in distributed. We present a data fusion scheme for use in mobile wireless sensor networks with high energy efficiency and low network delays, that still produces reliable results. Data fusion improves the coverage of wireless sensor. However, in comparison to traditional clientserver paradigm. Scalable structurefree data fusion on wireless sensor. Reliable data fusion in wireless sensor networks under. Sensor data, information, quality of information, wireless sensor networks.
This paper explores reliable data fusion in mobile access wireless sensor networks under byzantine attacks. The applications of the mwsns can be widely divided into timedriven, eventdriven, ondemand and. The wsn is built with nodes that are used to observe the surroundings like temperature, humidity, pressure, position, vibration, sound etc. This paper proposes a new data fusion approach which is based on the mobile agent technology. Multiple sensor based data fusion makes information more decisive, intelligent, sensible and precise than single sensor based data fusion. Location tracking in a wireless sensor network by mobile agents and its data fusion strategies 1 location tracking in a wireless sensor network by mobile agents and its data fusion strategies.
Research article tracking mobile robot in indoor wireless sensor networks lipingzhang, 1 chengchewlim, 2 yipingchen, 1 andhamidrezakarimi 3 college of electronic and electrical engineering, shanghai university of engineering science, song jiang district. The improved availability of sensor nodes has caused an increase in the number of researchers studying sensor networks. Tmmdf algorithm uses dixon method to eliminate negligent errors in the original data. Clientserver paradigm has been a commonly used computing model in traditional distributed sensor networks dsns.
A comprehensive data gathering network architecture in large. Advantages of data fusion disadvantages of data fusion. A data fusion method in wireless sensor networks article pdf available in sensors 15 2. It depends on the quantity of the transmitted data in the network for the level of the data transmission energy consumption. The expectation is that fused data is more informative and synthetic than the original inputs. Wireless sensor networks wsns are composed of a large number of spatially distributed autonomous sensor nodes. Quality of information in wireless sensor networks.
In wireless sensor network, data fusion or data aggregation is the key technology to decrease power consumption and improve accuracy of data collection. Wireless sensor networks wsns consist of large number of constrained wireless sensor nodes for the purpose of data gathering. 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. Wireless sensor networks wsns are formed of various nodes that gather. Location tracking in a wireless sensor network by mobile. Distributed detection in mobile access wireless sensor networks under byzantine attacks mai abdelhakim, leonard e. It has been characterised in a variety of ways, ranging from the description of its purposes, to reasonably abstract models of its processes and components. Wild life passer species recognition from a technical passage. One of the most important problems studied in any sensor network is data fusion. The main purpose of wireless sensor networks wsns is to obtain information about their environment. A fuzzy data fusion solution to enhance the qos and the energy.
An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks. Data fusion processes are often categorized as low, intermediate, or high, depending on the processing stage at which fusion takes place. The fundamental utility of the largescale visual sensor networks lvsns is to. Data fusion is the process of integrating multiple data sources to produce more consistent, accurate, and useful information than that provided by any individual data source data fusion processes are often categorized as low, intermediate, or high, depending on the processing stage at which fusion takes place. Mobile wireless sensor network mwsn is one of the rising and emerging technologies for various application of nwgn, the enormous concerns of these networks are data gathering with energy efficiency. A study on data fusion of wireless sensor networks security. Keywords wsn, data aggregation, data fusion, sensor network, iot i. For the characteristics of wireless sensor networks, combined the knowledge discover theory of data mining and knowledge application theory of data fusion, to set a unique integrated information treatment model based on neural network based aggregation. Mwsns are much more versatile than static sensor networks as they can be deployed in any scenario and cope with rapid topology changes. Wireless sensor networks are typically composed of lowcost sensors that are deeply integrated in physical environments.
In this section, we describe innetwork processing in wsn. 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. This paper introduces wireless sensor network data fusion concepts and roles, and it analyzes the data fusion in wireless sensor networks the major technical challenges. These sensor nodes monitor a physical environment situation such as temperature, motion or pressure etc. Download citation add to favorites reprints and permissions. Research article tracking mobile robot in indoor wireless. Recall that ri is the size of locally processed sensory. Synchronization of multiple levels of data fusion in. Mwsns are a budding field of research in contrast to their wellestablished ancestor. Healing coverage holes for big data collection in largescale. 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. Introduction a wireless sensor network is a network which comprises of a number of small autonomous sensor nodes called motes.
Among many feasible data sources, wireless sensor networks. However, the deployment of wireless sensor networks wsns and its ad hoc nature have brought new challenges to the fusion. In order to reduce the data processing load on bs and efficiently distinguish the authenticity of archived data, izadi et al. Mobile leach operations are very similar to the static leach operations. Mobile wireless sensor networks mwsns have emerged and shifted the focus from the typical static wireless sensor networks to networks with mobile sensor nodes that are capable to sense the various types of events. Wireless sensor network wsn architecture and applications. Synchronization of multiple levels of data fusion in wireless sensor networks wei yuan, srikanth v.
Wireless sensor networks wsns are a distributed collection of sensor. The paper exploiting optimal threshold for decision fusion in wireless sensor networks proposes a binary decision fusion scheme that reaches a global decision by integrating local decisions made by fusion members. 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. Mwsns are a smaller, emerging field of research in contrast to their wellestablished predecessor.
In signal based data fusion, fusion of information takes place at the sensor node or within local network. However, wsns often produce imprecise and incorrect sensor data, e. Design and analysis of a data fusion scheme in mobile. Introduction the data transmission causes a major part of the network energy consumption in wireless sensor networks wsns. Mobile leach is a mobilitycentric protocol which is designed for mobile wireless sensor networks. A novel data fusion strategy based on extreme learning.
Besides, there is a trend of the fusion of cellular networks with other wireless. Tt that all dispatched mobile nodes can transmit in their lifetime. Biologically inspired clustering algorithms in mobile wireless sensor networks. Data fusion is the process of integrating multiple data sources to produce more consistent, accurate, and useful information than that provided by any individual data source.
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. Wireless sensor networks for big data systems ncbi. Quality estimation based data fusion in wireless sensor networks abstract. Data fusion, data collection, mobile sink, rendezvous points rps, wireless sensor networks wsns. Many algorithms have been developed for data delivery and fusion in static microsensor networks, but most of them are not appropriate for mobile sensor networks.
Scalable and reliable data delivery in mobile ad hoc. Security mechanism of transmission encryption of network is introduced to protect the security of data. In addition the node clustering technique offers structural convenience for the data fusion. Data fusion in mobile wireless sensor networks muhammad arshad, member, iaeng, mohamad alsalem, farhan a. Citeseerx document details isaac councill, lee giles, pradeep teregowda. The optimal local thresholds and global threshold are derived by using the minmax criterion based analysis while they are ensuring false alarm rate constraint, without a preestimated target appearance probability. It uses mobile agent communication to decide the filtering or merging on data. Citeseerx optimal itinerary analysis for mobile agents. Mobile wireless sensor network mwsn is one of the rising and emerging technologies for various application of nwgn, the enormous concerns of these networks are data. In this paper, a fuzzybased solution for data fusion in wsns is presented to. An intelligent data gathering schema with data fusion supported for.
Online bayesian data fusion in environment monitoring sensor networks. To avoid this problem, wireless sensor network in the process of data collection need to adopt data fusion data aggregation or data fusion technology. Data fusion improves the coverage of wireless sensor networks. Different from the optimization in the conventional wireless sensor. Sensor networks generate continuous stream of data over time. Wireless sensor networks in monitoring the environmental activities grows and this. Saad, nasrullah armi, nidal kamel abstractduring the last decades. Lightfoot, jian ren, senior member, ieee, and tongtong li abstractthis paper explores reliable data fusion in mobile access wireless sensor networks under byzantine attacks. An overview of information extraction from mobile wireless. Wireless sensor network wsn with mobile sink serves a lot of industrial and agricultural monitoring applications. Localization based on magnetic and rss data fusion with. The data fusion in the network based on the data compression technique could efficiently reduce the amount of the data. Distributed detection in mobile access wireless sensor.
In addition, the gating technique is also applied to solve the problem of msdft mobile sensor data fusion tracking for targets, i. It depends on the quantity of the transmitted data in the. Research on network data fusion based on wireless sensor. An intelligent data gathering schema with data fusion. Wsns measure environmental conditions like temperature, sound, pollution levels, humidity, wind, and so on. Benefits or advantages of data fusion following are the benefits or advantages of data fusion. But, the mobile leach allows the inclusion of the mobile sensor nodes with noncluster heads on a setup phase and also rearrange the cluster of minimum energy consumption. In order to effectively reduce the redundant information transmission in the network, a data fusion algorithm based on extreme learning machine optimized by bat algorithm for mobile heterogeneous wireless sensor networks is proposed. Also, they can change their position frequently in a specific sensing area.
Proceedings of the 15th annual international conference on mobile computing and networking data fusion improves the coverage of wireless sensor networks. In wireless sensor networks wsns, mobile agent ma is a new paradigm that has gained more attention lately. Wireless sensor network wsn refers to a group of spatially dispersed and dedicated sensors for monitoring and recording the physical conditions of the environment and organizing the collected data at a central location. Wireless sensor network in which nodes are mobile can be defined as mwsn mobile wireless sensor networks. This paper studies scalable data delivery algorithms in mobile ad hoc sensor networks with node and link failures. Following are the benefits or advantages of data fusion. Design and analysis of a data fusion scheme in mobile wireless. Emerging machine learning technology provides a novel direction for data fusion and makes it more available and intelligent. Big data analytics for large scale wireless networks arxiv. The model is effective on saving wireless sensor energy consumption, extends net life, and is applicable to a variety of 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. Pdf wireless sensor networks for monitoring the environmental. Improved data fusion model for wireless sensor network. Although, monitoring was the initial application of wireless sensor networks, in network data processing and near realtime actuation capability have made wireless sensor networks suitable candidate for event detection and alarming applications as well. Systemlevel calibration for data fusion in wireless. The third year of the psi project was marked with increased effort in translating research ideas to fullfledged prototype development in overlapping domains of wireless sensor networks, computer and network security, pervasive computing, machine learning, and databases. This paper gives a survey on classical data fusion in wireless sensor networks from the following aspects. Distributed detection and fusion in a large wireless sensor network of random size. Multisensory data fusion alludes to the synergistic blend of tactile information from. A mobile wireless sensor network mwsn can simply be defined as a wireless sensor network wsn in which the sensor nodes are mobile. Data fusion is an important method for saving energy in wireless sensor networks wsns. 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. Recently, wireless sensor networks wsn community has witnessed an application focus shift. These are similar to wireless ad hoc networks in the sense that.
Lowlevel data fusion combines several sources of raw data to produce new raw data. 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. An algorithm of mobile sensors data fusion tracking for. Sensor fusionbased event detection in wireless sensor. Energy efficient computation of data fusion in wireless sensor networks using cuckoo based particle. As a result, the sensing performance of a wireless sensor network is inevitably undermined by biases in imperfect sensor hardware and the noises in data measurements.
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