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.

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)

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.

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.

Optical local area network emulations over Ethernet passive optical networks:A survey

As a promising solution to efficiently achieving fiber to the home （FTTH）, Ethernet passive optical network （EPON） is currently improved to provide intercommunication among customers, together with normal traffic delivery, via optical local area network emulation. It is a new research direction and expected to enhance the normal EPON performances. The purpose of this article is to review the state-of -the-art solutions to emulating optical local area networks （OLANs） over EPON. We discuss the major problems involved, e.g., network architecture, control mechanisms, and other potential enhancements. We also outline areas for future researches.

Multiusers Parallel Competitive Channel Protocol Based on Unsaturated Service

In order to enhance the area throughput of next generation wireless local area network(WLAN)in high density scenarios,orthogonal frequency division multiple access(OFDMA)has been adopted as one of the key technologies in the next generation WLAN communication standards.However,the performance of the existing media access control(MAC)degrades significantly under unsaturated services.Therefore,this paper proposes a multi-user parallel contention channel MAC(MU-MAC)based on unsaturated services,which can effectively reduce the channel access conflict and improve the OFDMA access efficiency of cluster member nodes.On this basis,MU-MAC is enhanced for the spatial clustering group(SCG)formation protocol and support for the unsaturated service characteristics.Further,the optimal access radius when the service is in a non-saturated state is analyzed to make the relevant theoretical analysis more generally,and the expressions for the throughput and area throughput of the proposed protocol are modeled and derived.The simulation results verify the correctness of the theoretical analysis and the efficiency of the protocol performance.The results show that MU-MAC outperforms IEEE 802.11ax and OMAX protocol in area throughput by 40.72%and 104.15%,respectively.

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.

SEM-Based Method for Performance Evaluation of Wired LANs

For wired local area networks(LANs),their effectiveness and invulnerability are very critical.It is extraordinarily significant to evaluate the network performance effectively in the design of a reasonable network topology and the performance improvement of the networks.However,there are many factors affecting the performance of the networks,and the relation among them is also complicated.How to evaluate the performance of the wired LANs more accurately has been a heavy challenge in the network research.In order to solve the problem,this paper presents a performance evaluation method that evaluates the effectiveness and invulnerability of the wired LANs.Compared to traditional statistical methods,it has the distinct advantage of being able to handle several dependent variables simultaneously and tolerates the measurement errors among these independent variables and dependent variables.Finally,the rationality and validity of this method are verified by the extensive experimental simulation.

Improved MIMO-OFDM scheme for the next generation WLAN

The research and application of wireless local area networks （WLAN） technology are in a stage of rapid development. It has been one of research focuses of the wireless communications field. Through the use of enhanced single-user （SU）/multi-user （MU） multiple input multiple output （MIMO）-orthogonal frequency division multiplexing （OFDM） technology, the next generation WLAN IEEE 802.1 lac dramatically increases the throughput. An improved MIMO-OFDM scheme based on modulation diversity is proposed for the next generation WLAN. It uses two-dimensional modulation diversity to the current IEEE 802.11ac transmission scheme. Through the space-time-frequency component inter- leaver and the rotational modulation, the proposed scheme ex- hibits high spectral efficiency and low error rate in fading channels. The simulation results show that the proposed scheme significantly outperforms the SU/MU MIMO-OFDM scheme in the current IEEE 802.11 ac standard, which is up to 5 dB.

Research and Development of Indoor Positioning

Indoor positioning systems have been sufficiently researched to provide location information of persons and devices.This paper is focused on the current research and further development of indoor positioning.The standard evolution and industry development are summarized.There are various positioning systems according to the scenarios,cost and accuracy.However,there is a basic positioning system framework including information extraction,measurement and calculation.In particular,the detailed positioning technologies mainly including cellular positioning and Local Area Network(LAN) positioning are listed and compared to provide a reference for practical applications.Finally,we summarize the challenges of indoor positioning and give a3-phase evolution route.

Modeling and Simulation of P-Aloha,CSMA /CA and MACAW Protocols for Underwater Acoustic Channel

Medium access control( MAC) protocol of underwater acoustic communication network is a key technology for underwater acoustic networks( UANs). Most of the MAC protocols for wireless terrestrial communication networks have been designed with negligible propagation delay. If it is deployed directly in an underwater environment,the UANs will perform inefficiently. In this paper,the characteristics of underwater acoustic channel are modeled and simulated by using the OPNET simulation tool,which are the speed of sound, propagation loss, and four sources for ambient noise: the turbulence,shipping,wind driven waves and thermal noise. The performance of pure Aloha( P-Aloha),carrier sense multiple access with collision avoidance( CSMA / CA) and multiple access collision avoidance for wireless local area network( MACAW) protocols in underwater acoustic channel environment are evaluated. The different performance of protocols in underwater environment is compared in the simulation.

Adaptive rate control on wireless transcoder

To guarantee the real-time transmission of a video stream, based on the stochastic optimal control method, a frame layer adaptive rate control algorithm for the wireless transcoder is proposed, which is capable of dynamically determining the transcoder＇s objective bit rate, according to the bandwidth variation of the wireless channel and the buffer occupancy. Then the transient performance, steady performance, and computational complexity of the algorithm are analyzed. Finally, the experiment results demonstrate that the algorithm can improve the synthetic performance of rate control through the compromise between the end-to-end delay and the playout quality.

Semi-Supervised Clustering Fingerprint Positioning Algorithm Based on Distance Constraints

With the rapid development of WLAN( Wireless Local Area Network) technology,an important target of indoor positioning systems is to improve the positioning accuracy while reducing the online computation.In this paper,it proposes a novel fingerprint positioning algorithm known as semi-supervised affinity propagation clustering based on distance function constraints. We show that by employing affinity propagation techniques,it is able to use a fractional labeled data to adjust similarity matrix of signal space to cluster reference points with high accuracy. The semi-supervised APC uses a combination of machine learning,clustering analysis and fingerprinting algorithm. By collecting data and testing our algorithm in a realistic indoor WLAN environment,the experimental results indicate that the proposed algorithm can improve positioning accuracy while reduce the online localization computation,as compared with the widely used K nearest neighbor and maximum likelihood estimation algorithms.

Partially Overlapping Channel Assignment Using Bonded and Non-Bonded Channels in IEEE 802.11n WLAN

Nowadays,wireless local area network(WLAN)has become prevalent Internet access due to its low-cost gadgets,flexible coverage and hasslefree simple wireless installation.WLAN facilitates wireless Internet services to users with mobile devices like smart phones,tablets,and laptops through deployment of multiple access points(APs)in a network field.Every AP operates on a frequency band called channel.Popular wireless standard such as IEEE 802.11n has a limited number of channels where frequency spectrum of adjacent channels overlaps partially with each other.In a crowded environment,users may experience poor Internet services due to channel collision i.e.,interference from surrounding APs that affects the performance of the WLAN system.Therefore,it becomes a challenge to maintain expected performance in a crowded environment.A mathematical model of throughput considering interferences from surrounding APs can play an important role to set up a WLAN system properly.While set up,assignment of channels considering interference can maximize network performance.In this paper,we investigate the signal propagation of APs under interference of partially overlapping channels for both bonded and non-bonded channels.Then,a throughput estimation model is proposed using difference of operating channels and received signal strength indicator(RSSI).Then,a channel assignment algorithm is introduced using proposed throughput estimation model.Finally,the efficiency of the proposal is verified by numerical experiments using simulator.The results show that the proposal selects the best channel combination of bonded and non-bonded channels that maximize the performance.

Simulation model based on Monte Carlo method for traffic assignment in local area road network

For a local area road network,the available traffic data of traveling are the flow volumes in the key intersections,not the complete OD matrix.Considering the circumstance characteristic and the data availability of a local area road network,a new model for traffic assignment based on Monte Carlo simulation of intersection turning movement is provided in this paper.For good stability in temporal sequence,turning ratio is adopted as the important parameter of this model.The formulation for local area road network assignment problems is proposed on the assumption of random turning behavior.The traffic assignment model based on the Monte Carlo method has been used in traffic analysis for an actual urban road network.The results comparing surveying traffic flow data and determining flow data by the previous model verify the applicability and validity of the proposed methodology.

Resource Allocation for Uplink CSI Sensing Report in Multi-User WLAN Sensing

Sensing in wireless local area network(WLAN) gains great interests recently. In this paper we focus on the multi-user WLAN sensing problem under the existing 802.11 standards. Multiple stations perform sensing with the access point and transmit channel state information(CSI)report simultaneously on the basis of uplink-orthogonal frequency division multiple access(OFDMA). Considering the transmission resource consumed in CSI report and the padding wastage in OFDMA based CSI report, we optimize the CSI simplification and uplink resource unit(RU)allocation jointly, aiming to balance the sensing accuracy and padding wastage performances in WLAN sensing. We propose the minimize padding maximize efficiency(MPME) algorithm to solve the problem and evaluate the performance of the proposed algorithm through extensive simulations.

Indoor localization via l^1-graph regularized semi-supervised manifold learning

In this paper, a new -graph regularized semi-supervised manifold learning （LRSML） method is proposed for indoor localization. Due to noise corruption and non-linearity of received signal strength （RSS）, traditional approaches always fail to deliver accurate positioning results. The -graph is constructed by sparse representation of each sample with respect to remaining samples. Noise factor is considered in the construction process of -graph, leading to more robustness compared to traditional k-nearest-neighbor graph （KNN-graph）. The KNN-graph construction is supervised, while the -graph is assumed to be unsupervised without harnessing any data label information and uncovers the underlying sparse relationship of each data. Combining KNN-graph and -graph, both labeled and unlabeled information are utilized, so the LRSML method has the potential to convey more discriminative information compared to conventional methods. To overcome the non-linearity of RSS, kernel-based manifold learning method （K-LRSML） is employed through mapping the original signal data to a higher dimension Hilbert space. The efficiency and superiority of LRSML over current state of art methods are verified with extensive experiments on real data.

Experimental demonstration of multigranularity switching between optical DFT-spread-OFDM and Nyquist superchannel

We experimentally investigate multigranularity optical subband switching functionality between two superchannels with slight error vector magnitude penalty. One is 4×39 Gb/s polarization-division-multiplexed（PDM） quadrature phase shift keying discrete Fourier transform spread orthogonal frequency division multiplexing（DFT-spread-OFDM） superchannel with 12.5 GHz band spacing. The other is 8×29 Gb/s PDM-16-quadrature amplitude modulation Nyquist pulse shaping superchannel with 6.25 GHz band spacing. To the best of our knowledge, this is the first time that optical switching functionality for individual band between different superchannels with multigranularity is realized.

Full-duplex transmission of IEEE 802.11ac-compliant MIMO WLAN signals over a 2-km 7-core fiber

In this Letter, we experimentally demonstrate a full-duplex transmission system of IEEE 802.11ac-compliant multiple-input multiple-output （MIMO） signals over a 2-kin 7-core fiber for in-building wireless local-area net- work （WLAN） distributed antenna systems. For full-duplex 3 x 3 MIMO demonstration, the crosstalk impacts of both fiber-transmission-only and optic-wireless transmission situation are evaluated. The results indicate that the impact of crosstalk on radio-over-fiber （ROF） link performance is not significant and the quality of the cascaded multi-core fiber and wireless channel is mainly determined by the wireless part. To further improve the system capacity, polarization multiplexing （PolMux） technology is employed to achieve a full-duplex 6 × 6 MIMO over a single 7-core fiber. Although employing the PolMux method will slightly decrease the EVM and condition number performance as opposed to a non-PolMux MCF system, it is still a competitive solution in large optical connection demand scenarios that require a low cost.

Joint scheme for symbol,sampling clock,and carrier frequency synchronization in PDM-CO-OFDM system beyond 100 Gb/s

We propose a joint scheme for symbol, sampling clock, and carrier frequency synchronization in a polarization division multiplexing coherent optical orthogonal frequency division multiplexing （PDM-CO-OFDM） system. Unlike other existing algorithms designed for specific impairment, the scheme can estimate and compensate for the interactional synchronization errors effectively without extra training overhead by building a comprehensive error model. The simulation shows that symbol synchronization error and sample timing error can be corrected by channel equalizer, and the estimation ranges of sampling frequency offset and normalized carrier frequency offset are about （-2000, 2000） ppm, and （-0.04 （-3.5）, 0.04 （3.5）） Ghz, respectively.