浅议无线传感器网络技术

传感器技术、分布式信息处理技术、无线通信技术、片上系统（SOC）技术、低功耗嵌入式计算技术、微机电系统（MEMS）技术的飞速发展,孕育出了无线传感器网络（WSN）,WSN以其低功耗、低成本、分布式和自组织等特点带来信息感知技术的进步。WSN是由部署在监测区域内大量传感器节点,以自组织．多跳和无线通信方式构成的无线网络系统,用于协作地实时监测、感知、采集、处理、控制和传输网络覆盖区域中被感知对象的信息,并发送给观察者或网络所有者。     

无线传感器网络在应急通信系统中的应用

无线传感器网络是一个全新的研究领域，它综合了传感器技术、嵌入式计算技术、分布式信息处理技术和无线通信技术，应用前景十分广泛，已经成为目前的一个研究热点。无线传感器具有高可靠性、高抗毁性、随需而设、即设即用等特点，尤其适合用来完成应急系统中对无法部署固定线路的突发公共安全事件的监测任务。本文首先对无线传感器网络的体系结构进行了介绍，然后探讨了无线传感器网络需要解决的关键问题，最后设计了面向应急的无线传感器网络信息服务系统，实现了应急系统与无线传感器网络的结合。     

LEACH算法的改进分簇模型在无线传感器网络中的研究

无线传感器网络是将传感器通过无线通信的方式,对网络信息进行处理及传递.网络综合了传感器技术、嵌入式计算技术、分布式信息处理技术和通信技术,可以实时监测、感知和采集网络分布区域内的各种对象的信息,并对这些信息进行处理,传送给所需用户.LEACH算法是一种典型的层次路由算法,该算法提出了低功耗持续运行的模型.但LEACH算...     

无线传感器网络的崛起

无线传感器网络综合了微电子、嵌入式计算、现代网络及无线通信、分布式信息处理等先进技术,能够协同地实时监测、感知和采集网络覆盖区域中各种环境或监测对象的信息,并对其进行处理,处理后的信息通过无线方式发送,并以自组多跳的网络方式传送给观察者.     

无线传感器网络的体系结构及其应用

无线传感器网络(WSN)综合了传感器技术,微机电系统(MEMS)、嵌入式技术、网络通信技术和分布式信息处理等技术,是集信息采集、信息传输、信息处理于一体的综合智能信息系统.本文主要介绍了无线传感器网络的体系结构、传感器节点的组成、无线传感器网络的协议栈、特点和应用.     

浅谈无线传感器网络的平台开发与组网技术

无线传感器网络有着许多特点和优点,一是具有功耗低、成本低的优点;二是具有分布式和自组织的特点。除此之外,它还具有采集信息、传输信息和处理信息的功能。目前,随着无线传感器网络的广泛应用,人们对无线传感器网络平台及其组网方式上的研究和开发越来越重视。本文从无线传感器网络的理论研究出发,介绍了其平台开发和组网的国内外技术研究现状和发展方向,并提出了无线传感器网络开发平台和组网方式选择方法。     

无线传感器网络在农业信息化中的应用研究

无线传感器网络是计算机科学与自动化技术研究的一个热点问题,它综合了传感器技术、通信技术与微处理器技术,在当前农业信息化的发展中具有良好的应用前景。无线传感器网络适合温室、田间、动植物生长环境中信息的监测与采集。为农业信息化的有效应用提供信息采集、处理与决策的方案。本文介绍了无线传感器网络技术的网络结构、传感器节点构成与通信协议,分析了无线传感器网络在温室种植、农作物生长环境监测、节水滴灌技术、生物习性监测等方面的应用,探讨了无线传感器网络在农业信息化中的应用特点和研究进展。     

无线传感器网络及应用研究

随着微电子技术、计算机技术、无线通信和传感器技术的飞速发展和日益成熟,无线传感器网络得到迅速发展.无线传感器网络能实时监测、感知、采集和处理各种监测对象信息,已经成为了科学研究领域最前沿的课题之一.文章主要介绍了无线传感器网络的概念、结构、特点及其在一些领域的应用,并展望了无线传感器网络未来发展.     

浅谈无线传感网络技术

1 无线传感器网络概述及其特点 无线传感器网络(Wireless Sensor Network,WSN)是一种新的科学技术网络,该研究始于美国军方.它是由大量具有特殊作用的无线传感器节点,通过自组织的方式进行信息传递,互相协作完成特定功能的智能型网络.它结合了微机电系统、传感器技术、嵌入式计算技术、现代网络及无线通信技术,通过集成微传感器对各类分布式信息处理技术和软件编程技术实时协作,对各种环境实时监控,将监测对象控制地区采集到的数据聚集,通过自组织多跳网络的方式传送给用户终端,从而实现物理世界、计算机世界和人类世界社会的三元连接.     

三种无线分布式网络的比较

无线分布式网络近年来受到了越来越广泛的关注,adhoc网络、无线传感器网络和无线Mesh网络是目前无线分布式网络中最具代表性的3种类型。本文着重对这3种无线分布式网络的基本概念、技术特点和应用场合进行了分析研究和比较。     

无线传感器网络技术

无线传感器网络是新兴网络,它采用无线通信技术,由微小的传感器组成,无线传感器网络节点具备感应能力、信息处理能力和无线通信能力,使无线传感器网络有广阔的应用前景,可广泛用于军事、环境、医疗保健、空间探索及各种商业应用。无线传感器网络是新的研究领域,文中分析了无线传感器网络研究中的热点问题,讨论了无线传感器网络的应用,展望了无线传感器网络的美好前景。     

Outlier Detection in Wireless Sensor Networks Based on Neighbourhood

Wireless sensor networks contain millions of nodes deployed in a spatially dispersed manner. These sensors are low battery powered devices having limited storage and computation power. The data collected by these sensors may be subjected to error due to environmental fluctuations, interference in wireless communication or wearing of sensors with time. These erroneous data deviate significantly from the rest of the data. To solve this issue, we present a new technique named Outlierness Factor based on Neighbourhood to detect and analyse the outliers in sensor network. Proposed detection approach is time efficient and scalable. Further, outlier data are classified as errors due to sensor malfunctioning or actual detected events such as fire detection, weather changes, earthquakes, landslide etc. The capabilities of the proposed approach have been evaluated on real dataset obtained from Intel Berkeley research lab and synthetic datasets. The results show the effectiveness of the proposed approach in contrast to the previously dealt approaches.

     

Network Partitioning Recovery Mechanisms in WSANs: a Survey

Wireless sensor and actor networks (WSANs) are more promising and most addressing research field in the area of wireless sensor networks in recent scenario. It composed of possibly a large number of tiny, autonomous sensor devices and resources rich actor nodes equipped with wireless communication and computation capabilities. Actors collect sensors’ information and respond collaboratively to achieve an application specific mission. Since actors have to coordinate their operation, a strongly connected inter-actor network would be required at all the time in the network. Actor nodes may fail for many reasons (i.e. due of battery exhaustion or hardware failure due to hash environment etc.) and failures may convert connected network into disjoint networks. This can hinder sometimes not only the performance of network but also degrade the usefulness and effectiveness of the network. Thus, having a partitioning detection and connectivity restoration procedure at the time of failure occurs in the network is crucial for WSANs. In this paper, we review the present network partitioning recovery approaches and provide an overall view of this study by summarizing previous achievements.     

Target localization based on energy considerations in distributed sensor networks

Wireless distributed sensor networks are important for a number of strategic applications such as coordinated target detection, surveillance, and localization. Energy is a critical resource in wireless sensor networks and system lifetime needs to be prolonged through the use of energy-conscious sensing strategies during system operation. We propose an energy-aware target detection and localization strategy for cluster-based wireless sensor networks. The proposed method is based on an a posteriori algorithm with a two-step communication protocol between the cluster head and the sensors within the cluster. Based on a limited amount of data received from the sensor nodes, the cluster head executes a localization procedure to determine the subset of sensors that must be queried for detailed target information. This approach reduces both energy consumption and communication bandwidth requirements, and prolongs the lifetime of the wireless sensor network. Simulation results show that a large amount of energy is saved during target localization using this strategy.     

Plug ‘n Play Simplicity for Wireless Medical Body Sensors

Wireless medical body sensors are a key technology for unobtrusive health monitoring. The easy setup of such wireless body area networks is crucial to protect the user from the complexity of these systems. But automatically forming a wireless network comprising all sensors attached to the same body is challenging. We present a method for making wireless body-worn medical sensors aware of the persons they belong to by combining body-coupled with wireless communication. This enables a user to create a wireless body sensor network by just sticking the sensors to her body. A personal identifier allows sensors to annotate their readings with a user ID thereby ensuring safety in personal healthcare environments with multiple users.     

A Supervised Learning Based Decision Support System for Multi-Sensor Healthcare Data from Wireless Body Sensor Networks

Wireless body sensor network (WBSN) is also known as wearable sensors with transmission capabilities, computation, storage and sensing. In this paper, a supervised learning based decision support system for multi sensor (MS) healthcare data from wireless body sensor networks (WBSN) is proposed. Here, data fusion ensemble scheme is developed along with medical data which is obtained from body sensor networks. Ensemble classifier is taken the fusion data as an input for heart disease prediction. Feature selection is done by the squirrel search algorithm which is used to remove the irrelevant features. From the sensor activity data, we utilized the modified deep belief network (M-DBN) for the prediction of heart diseases. This work is implemented by Python platform and the performance is carried out of both proposed and existing methods. Our proposed M-DBN technique is compared with various existing techniques such as Deep Belief Network, Artificial Neural Network and Conventional Neural Network. The performance of accuracy, recall, precision, F1 score, false positive rate, false negative and true negative are taken for both proposed and existing methods. Our proposed performance values for accuracy (95%), precision (98%), and recall (90%), F1 score (93%), false positive (72%), false negative (98%) and true negative (98%).

     

Optimum Temporal Coverage with Rotating Directional Sensors

Wireless Personal Communications - Advances in directional sensors technology and impressive development of wireless sensor networks, created a new class of wireless sensor networks called...     

Analysis and modeling of task scheduling in wireless sensor network based on divisible load theory

In this paper, we propose a novel task scheduling algorithm (Divisible Task scheduling Algorithm for Wireless sensor networks (DTAW)) based on divisible load theory in heterogeneous wireless sensor networks to complete the tasks within the shortest possible time and reduce the sensors' energy‐consuming. In DTAW, the tasks are distributed to the wireless sensor network by the (SINK) on the basis of the processing and communication capacity of each sensor. After receiving the subtasks, the intracluster sensors carry out its tasks simultaneously and send the results to cluster head sequentially. By removing communication interference between each sensor, reduced task completion time and improved network resource utilization are achieved. Each cluster head simultaneously finishes sending fused data to the SINK after fusing the data obtained from intracluster sensors. In this way, the overlap between the task performing and communication phase would be much better. Simulation results are presented to demonstrate the impacts of different network parameters on the makespan and energy consumption. The results show that the algorithm enables to reasonably distribute tasks to each sensor and then effectively reduces the time‐consuming and energy‐consuming. Copyright © 2012 John Wiley & Sons, Ltd.     

Simple,secure, and lightweight mechanism for mutual authentication of nodes in tiny wireless sensor networks

Wireless sensor networks (WSNs) are widely used in large areas of applications; due to advancements in technology, very tiny sensors are readily available, and their usage reduces the cost. The mechanisms designed for wireless networks cannot be implied on networks with tiny nodes due to battery and computational constraints. Understanding the significance of security in WSNs and resource constraintness of tiny WSNs, we propose a node authentication mechanism for nodes in wireless sensor networks to avoid security attacks and establish secure communication between them. In the proposed mechanism, a base station (BS) generates a secret value and random value for each sensor node and stores at the node. The sensor node authenticates using secret value and random number. Random nonce ensures freshness, efficiency, and robustness. The proposed mechanism is lightweight cryptographic, hence requires very less computational, communication, and storage resources. Security analysis of the proposed mechanism could not detect any security attack on it, and the mechanism was found to incur less storage, communication, and computation overheads. Hence, the proposed mechanism is best suitable for wireless sensor networks with tiny nodes.