Application of Wireless Local Area Network Technology in Mobile Robot for Finned Tube Inspection

This paper introduces a novel robot for outer surface inspection of boiler tubes. The paper describes the hardware system, wireless communication strategy, communication procedure and system software of the robot. The WLAN technology is used in the robot. It solves the problem of shielding generated by iron boiler and 11Mbps bandwidth made it possible for video and control stream real-time transmit within the same channel. Though TCP/IP protocol is robust, serial server is a transparent channel but cannot detect error and retransmit the data. In order to improve the reliability of serial communication, a new communication protocol is proposed. Key words boiler tubes - mobile robotics - wireless local area network Project Supported by the National High-Tech Program (Grant No. 2002AA420080)

Research on the Teaching Reform of ＂Wireless Local Area Network＂ in the Background of＂Wireless Business Circle＂

This paper proposes the teaching reform of the ＂Wireless Local Area Network＂ in the background of ＂Wireless Business Circle＂ . At present, WLAN technology is becoming more and more mature, the application is then becoming more and more extensive, the campus network will grow rapidly on wireless LAN applications especially the research and higher education institutions on the wireless LAN demand is increasing with wireless LAN will have a very broad market development space. GIS business circle analysis model is to determine business enterprise location or expand their existing business outlets of information necessary to say on the map by G1S visual function of the model. This paper makes the combination of the mentioned items that will then and later influence the performance of the model.

Localized Coverage Connectivity Based on Shape and Area Using Mobile Sensor Robots in Wireless Sensor Networks

A wireless sensor network (WSN) is spatially distributing independent sensors to monitor physical and environmental characteristics such as temperature, sound, pressure and also provides different applications such as battlefield inspection and biological detection. The Constrained Motion and Sensor (CMS) Model represents the features and explain k-step reach ability testing to describe the states. The description and calculation based on CMS model does not solve the problem in mobile robots. The ADD framework based on monitoring radio measurements creates a threshold. But the methods are not effective in dynamic coverage of complex environment. In this paper, a Localized Coverage based on Shape and Area Detection (LCSAD) Framework is developed to increase the dynamic coverage using mobile robots. To facilitate the measurement in mobile robots, two algorithms are designed to identify the coverage area, (i.e.,) the area of a coverage hole or not. The two algorithms are Localized Geometric Voronoi Hexagon (LGVH) and Acquaintance Area Hexagon (AAH). LGVH senses all the shapes and it is simple to show all the boundary area nodes. AAH based algorithm simply takes directional information by locating the area of local and global convex points of coverage area. Both these algorithms are applied to WSN of random topologies. The simulation result shows that the proposed LCSAD framework attains minimal energy utilization, lesser waiting time, and also achieves higher scalability, throughput, delivery rate and 8% maximal coverage connectivity in sensor network compared to state-of-art works.

Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks

In recent times,real time wireless networks have found their applicability in several practical applications such as smart city,healthcare,surveillance,environmental monitoring,etc.At the same time,proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks.This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization(IM-EECNL)approach for real-time wireless networks.The proposed IM-EECNL technique involves two major processes namely node localization and clustering.Firstly,Chaotic Water Strider Algorithm based Node Localization(CWSANL)technique to determine the unknown position of the nodes.Secondly,an Oppositional Archimedes Optimization Algorithm based Clustering(OAOAC)technique is applied to accomplish energy efficiency in the network.Besides,the OAOAC technique derives afitness function comprising residual energy,distance to cluster heads(CHs),distance to base station(BS),and load.The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency.A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio(PDR)of 0.985.

Synchronization in Wireless Networks for Practical MIMO-OFDM Systems

In this paper a frequency offset estimation technique for Wireless Local Area and Wireless Metropolitan Ar- ea Networks is presented. For frequency offset estimation, we have applied a low-complexity frequency offset estimator for simple AWGN channels to fading channels for MIMO-OFDM systems. Simulation results have shown that the performance of the proposed estimator is better than the low complexity frequency offset estimator designed for AWGN channels.

A PHEMT Based Wideband LNA for Wireless Applications

This work is about the development of a super low noise amplifier with minimum power consumption and high gain for several wireless applications.The amplifier operates at frequency bands of 0.9-2.4 GHz and can be used in many applications like Wireless local area network(WLAN),WiFi,Bluetooth,ZigBee and Global System for mobile communications(GSM).This new design can be employed for the IEEE 802.15.4 standard in industrial,scientific and medical(ISM) Band.The enhancement mode pseudomorphic high electron mobility transistor PHEMT is used here due to its high linearity,better performance and less noisy operation.The common source inductive degeneration method is employed here to enhance the gain of amplifier.The amplifier produces a gain of more than 17 dB and noise figure of about 0.5 dB.The lower values of S11 and S22 reflect the accuracy of impedance matching network placed at the input and output sides of amplifier.Agilent Advance Design System(ADS) is used for the design and simulation purpose.Further the layout of design is developed on the FR4 substrate.

An adaptive joint source and channel coding scheme for H.264 video multicasting over wireless LAN

This paper proposes an adaptive joint source and channel coding scheme for H.264 video multicast over wireless LAN which takes into account the user topology changes and varying channel conditions of multiple users, and dynamically allocates available bandwidth between source coding and channel coding, with the goal to optimize the overall system performance. In particular, source resilience and error correction are considered jointly in the scheme to achieve the optimal performance. And a channel estimation algorithm based on the average packet loss rate and the variance of packet loss rate is proposed also. Two overall performance criteria for video multicast are investigated and experimental results are presented to show the improvement obtained by the scheme.

Domain adaptive methods for device diversity in indoor localization

To solve the problem of variations in radio frequency characteristics among different devices,transfer learning is applied to transform device diversity to domain adaptation in the indoor localization algorithm.A robust indoor localization algorithm based on the aligned fingerprints and ensemble learning called correlation alignment for localization(CALoc)is proposed with low computational complexity.The second-order statistical properties of fingerprints in the offline and online phase are needed to be aligned.The real-time online calibration method mitigates the impact of device heterogeneity largely.Without any time-consuming deep learning retraining process,CALoc online only needs 0.11 s.The effectiveness and efficiency of CALoc are verified by realistic experiments.The results show that compared to the traditional algorithms,a significant performance gain is achieved and that it achieves better positioning accuracy with a 19%improvement.

Resource Exhaustion Attack Detection Scheme for WLAN Using Artificial Neural Network

IEEE 802.11 Wi-Fi networks are prone to many denial of service(DoS)attacks due to vulnerabilities at the media access control(MAC)layer of the 802.11 protocol.Due to the data transmission nature of the wireless local area network(WLAN)through radio waves,its communication is exposed to the possibility of being attacked by illegitimate users.Moreover,the security design of the wireless structure is vulnerable to versatile attacks.For example,the attacker can imitate genuine features,rendering classificationbased methods inaccurate in differentiating between real and false messages.Althoughmany security standards have been proposed over the last decades to overcome many wireless network attacks,effectively detecting such attacks is crucial in today’s real-world applications.This paper presents a novel resource exhaustion attack detection scheme(READS)to detect resource exhaustion attacks effectively.The proposed scheme can differentiate between the genuine and fake management frames in the early stages of the attack such that access points can effectively mitigate the consequences of the attack.The scheme is built through learning from clustered samples using artificial neural networks to identify the genuine and rogue resource exhaustion management frames effectively and efficiently in theWLAN.The proposed scheme consists of four modules whichmake it capable to alleviates the attack impact more effectively than the related work.The experimental results show the effectiveness of the proposed technique by gaining an 89.11%improvement compared to the existing works in terms of detection.

A NOVEL LINK ADAPTATION SCHEME TO ENHANCE PERFORMANCE OF IEEE 802.11G WIRELESS LAN

A novel link adaptation scheme using linear Auto Regressive （AR） model channel estimation algorithm to enhance the performance of auto rate selection mechanism in IEEE 802.11g is proposed. This scheme can overcome the low efficiency caused by time interval between the time when Received Signal Strength （RSS） is measured and the time when rate is selected. The best rate is selected based on data payload length, frame retry count and the estimated RSS, which is estimated from recorded RSSs. Simulation results show that the proposed scheme enhances mean throughput performance up to 7%, in saturation state, and up to 24% in finite load state compared with those non-estimation schemes, performance enhancements in average drop rate and average number of transmission attempts per data frame delivery also validate the effectiveness of the proposed schelne.

基于Snort-wireless的分布式入侵检测系统研究与设计

为了解决无线局域网存在的安全隐患,该文设计了基于Snort-wireless的分布式入侵检测模型。该模型利用开源、免费和易于扩展的Snort-wireless实现客户端的网络入侵检测引擎,利用VC++开发了控制中心,并且采用加密的TCP/IP协议实现客户端与控制中心之间的安全通信。同时,该模型符合入侵检测的标准框架CIDF,使该模型在性能、重用性以及可扩展性方面得到保证。

Wireless-LAN安全及认证方法的研究与分析

首先介绍了无线局域网面临的安全问题,并对无线局域网的安全要求进行了分析;介绍了国内外Wire-less-LAN安全认证机制的研究现状,在此基础上详细分析了基于EAP的无线网络安全认证方法;最后对几种主要的认证方法进行了分析比较。

A shock wave overpressure test system based on WLAN

Due to short transmission distance and low transmission speed when testing the shock wave overpressure with storage test method based on ZigBee technology, a new test method based on wireless local area network （WLAN） technology is proposed, which can monitor remote test nodes. Moreover, the wireless network is designed based on 802. 11b/g protocol, which is helpful for reading the data of the test nodes quickly. Therefore, the accessibility of distributed test system can be improved greatly. The field test results show that the test system performance is good and the transmission speed is high.

基于Systemview的无线局域网直序扩频系统的研究与设计

目前扩频通信得到日益广泛的应用,对它进行系统建模与仿真非常有益.论述了在无线局域网(WLAN)环境中,基于IEEE802.11参考标准,采用科斯塔斯环路实现直接序列扩频通信系统的伪码同步与载波同步的方法,给出了Systemview平台下的仿真结果,详细展示了直序扩频系统工作的全过程,为设计和分析直序扩频通信系统提供了方便.

Influence of Error-prone Channel on the Performance of IEEE 802.11 WLAN Utilizing RTS/CTS Handshaking

A comprehensive study was presented for WLAN 802.11b using error-prone channel. It was theoretically and numerically evaluated the performance of three different network sizes with the bit rates that available in 802.11b protocol. Results show that throughput does not change with the size of the network for wide range of bit error rates (BERs) and the channel bit rates play a significant role in the main characteristics of the network. A comprehensive explanation has given for the phenomenon of the packet delay suppression at relatively high level of BERs in view of the size of the networks and the BERs. The effect length of the transmitting packets is also investigated.

A KNN-based two-step fuzzy clustering weighted algorithm for WLAN indoor positioning

Although k-nearest neighbors （KNN） is a popular fingerprint match algorithm for its simplicity and accuracy, because it is sensitive to the circumstances, a fuzzy c-means （FCM） clustering algorithm is applied to improve it. Thus, a KNN-based two-step FCM weighted （KTFW） algorithm for indoor positioning in wireless local area networks （WLAN） is presented in this paper. In KTFW algorithm, k reference points （RPs） chosen by KNN are clustered through FCM based on received signal strength （RSS） and location coordinates. The right clusters are chosen according to rules, so three sets of RPs are formed including the set of k RPs chosen by KNN and are given different weights. RPs supposed to have better contribution to positioning accuracy are given larger weights to improve the positioning accuracy. Simulation results indicate that KTFW generally outperforms KNN and its complexity is greatly reduced through providing initial clustering centers for FCM.

Radio map updated method based on subscriber locations in indoor WLAN localization

With the rapid development of wireless local area network （WLAN） technology, an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online calibration effort to overcome signal time-varying. A novel fingerprint positioning algorithm, known as the adaptive radio map with updated method based on hidden Markov model （HMM）, is proposed. It is shown that by using a collection of user traces that can be cheaply obtained, the proposed algorithm can take advantage of these data to update the labeled calibration data to further improve the position estimation accuracy. This algorithm is a combination of machine learning, information gain theory and fingerprinting. By collecting data and testing the algorithm in a realistic indoor WLAN environment, the experiment results indicate that, compared with the widely used K nearest neighbor algorithm, the proposed algorithm can improve the positioning accuracy while greatly reduce the calibration effort.

A Semi-Supervised WLAN Indoor Localization Method Based on l1-Graph Algorithm

For indoor location estimation based on received signal strength( RSS) in wireless local area networks( WLAN),in order to reduce the influence of noise on the positioning accuracy,a large number of RSS should be collected in offline phase. Therefore,collecting training data with positioning information is time consuming which becomes the bottleneck of WLAN indoor localization. In this paper,the traditional semisupervised learning method based on k-NN and ε-NN graph for reducing collection workload of offline phase are analyzed,and the result shows that the k-NN or ε-NN graph are sensitive to data noise,which limit the performance of semi-supervised learning WLAN indoor localization system. Aiming at the above problem,it proposes a l1-graph-algorithm-based semi-supervised learning( LG-SSL) indoor localization method in which the graph is built by l1-norm algorithm. In our system,it firstly labels the unlabeled data using LG-SSL and labeled data to build the Radio Map in offline training phase,and then uses LG-SSL to estimate user's location in online phase. Extensive experimental results show that,benefit from the robustness to noise and sparsity ofl1-graph,LG-SSL exhibits superior performance by effectively reducing the collection workload in offline phase and improving localization accuracy in online phase.

Security Analysis of Application Layer Protocols on Wireless Local Area Networks

This paper aims at analyzing the security issues that lie in the application layer (AL) protocols when users connect to the Internet via a wireless local area network (WLAN) through an access point. When adversaries launch deauthentication flood attacks cutting users' connection, the connection managers will automatically research the last access point's extended service set identifier (ESSID) and then re-establish connection. However, such re-connection can lead the users to a fake access point with the same ESSID set by attackers. As the attackers hide behind users' access points, they can pass AL's authentication and security schemes, e.g. secure socket layer (SSL). We have proved that they can even spy on users' account details, passwords, data and privacy.

Secure Authentication of WLAN Based on Elliptic Curve Cryptosystem

The security of wireless local area network （WI.AN） becomes a bottleneck for its further applications. At present, many standard organizations and manufacturers of WLAN try to solve this problem. However, owing to the serious secure leak in IEEES02.11 standards, it is impossible to utterly solve the problem by simply adding some remedies. Based on the analysis on the security mechanism of WLAN and the latest techniques of WI.AN security, a solution to WLAN security was presented. The solution makes preparation for the further combination of WLAN and Internet.