Vehicular ad hoc networks (VANETs) have attracted a lot of attention in the research community in recent years due to their promising applications. VANETs help improve traffic safety and efficiency. Each vehicle can exchange information to inform other vehicles about the current status of the traffic flow or a dangerous situation such as an accident. Road safety and traffic management applications require a reliable communication scheme with minimal transmission collisions, which thus increase the need for an efficient medium access control (MAC) protocol. However, the design of the MAC in a vehicular network is a challenging task due to the high speed of the nodes, the frequent changes in topology, the lack of an infrastructure, and various QoS requirements. Recently, several time-division multiple-access (TDMA)-based MAC protocols have been proposed for VANETs in an attempt to ensure that all the vehicles have enough time to send safety messages without collisions and to reduce the end-to-end delay and the packet loss ratio. In this paper, we identify the reasons for using the collision-free MAC paradigm in VANETs. We then present a novel topology-based classification, and we provide an overview of TDMA-based MAC protocols that have been proposed for VANETs. We focus on the characteristics of these protocols, as well as on their benefits and limitations. Finally, we give a qualitative comparison, and we discuss some open issues that need to be tackled in future studies in order to improve the performance of TDMA-based MAC protocols for vehicle-to-vehicle communications.

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TDMA-Based MAC Protocols for Vehicular Ad Hoc Networks: A Survey, Qualitative Analysis, and Open Research Issues

Vehicular Ad hoc Networks (VANETs) have emerged recently as one of the most attractive topics for researchers and automotive industries due to their tremendous potential to improve traffic safety, efficiency and other added services. However, VANETs are themselves vulnerable against attacks that can directly lead to the corruption of networks and then possibly provoke big losses of time, money, and even lives. This paper presents a survey of VANETs attacks and solutions in carefully considering other similar works as well as updating new attacks and categorizing them into different classes.

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Security attacks and solutions in vehicular ad hoc networks : a survey

Service-oriented architecture (SOA) is gaining momentum as an emerging distributed system architecture for business-to-business collaborations. This momentum can be observed in both industry and academic research. SOA presents new challenges and opportunities for testing and verification, leading to an upsurge in research. This paper surveys the previous work undertaken on testing and verification of service-centric systems, which in total are 177 papers, showing the strengths and weaknesses of current strategies and testing tools and identifying issues for future work. Copyright © 2012 John Wiley & Sons, Ltd.

Testing and verification in service-oriented architecture: a survey

A scalable distributed machine learning approach for attack detection in edge computing environments

Our work in this paper presents a prediction of quality of experience based on full reference parametric (SSIM, VQM) and application metrics (resolution, bit rate, frame rate) in SDN networks. First, we used DCR (Degradation Category Rating) as subjective method to build the training model and validation, this method is based on not only the quality of received video but also the original video but all subjective methods are too expensive, don't take place in real time and takes much time for example our method takes three hours to determine the average MOS (Mean Opinion Score). That's why we proposed novel method based on machine learning algorithms to obtain the quality of experience in an objective manner. Previous researches in this field help us to use four algorithms: Decision Tree (DT), Neural Network, K nearest neighbors KNN and Random Forest RF thanks to their efficiency. We have used two metrics recommended by VQEG group to assess the best algorithm: Pearson correlation coefficient r and Root-Mean-Square-Error RMSE. The last part of the paper describes environment based on: Weka to analyze ML algorithms, MSU tool to calculate SSIM and VQM and Mininet for the SDN simulation.

Machine learning based QoE prediction in SDN networks

Quality of experience (QoE) in multimedia traffic has been the focus of extensive research in the last decade. The estimation of the QoE provides valuable input in order to measure the user satisfaction of a particular service. QoE estimation is challenging as it tries to measure a subjective metric where the user experience depends on a number of factors that cannot simply be measured. In this work, we present a methodology and a system based on fuzzy expert system to estimate the impact of network conditions (QoS) on the QoE of video traffic. At first, we conducted subjective tests to correlate network QoS metrics with participants' perceived QoE of video traffic. Second, we propose a No Reference method based on fuzzy expert system to estimate the network impact on the video QoE. The membership functions of the proposed fuzzy system are derived from normalized probability distributions correlating the QoS metrics with QoE. We propose a simple methodology to build the fuzzy inference rules. We evaluated our system in two different sets of experiments. The estimated video quality showed high correlation with the subjective QoE obtained from the participants in a controlled test. We integrated our system as part of a monitoring tool in an industrial IPTV test bed and compared its output with standard Video Quality Monitoring (VQM). The evaluation results show that the proposed video quality estimation method based on fuzzy expert system can effectively measure the network impact on the QoE.

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Estimation of QoE of video traffic using a fuzzy expert system

The service-oriented approach is becoming more and more popular to integrate highly heterogeneous systems. Web services are the natural evolution of conventional middleware technologies to support Web-based and enterprise level integration. Formal testing of such Web-based technology is a key point to guarantee its reliability. In this paper, we choose a non-intrusive approach based on monitoring to propose a conformance passive testing methodology to check that a composed Web service respects its functional requirements. This methodology is based on a set of formal invariants representing properties to be tested including data and time constraints. Passive testing of an industrial system (that uses a composition of Web services) is briefly presented to demonstrate the effectiveness of the proposed approach.

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Timed Extended Invariants for the Passive Testing of Web Services

MMT (Mont image Monitoring Tool) is a monitoring solution that combines: data capture, filtering and storage, events extraction, statistics collection, traffic analysis and reporting. In the context of the PIMI and DIAMONDS projects, Mont image is developing MMT-Security: a security analysis solution (part of MMT) that inspects network traffic against a set of security properties denoting both security rules and attacks. This tool has been applied to an industrial case study provided by Thales Group that consists of a QoS-aware ad-hoc radio communication protocol.

Events-Based Security Monitoring Using MMT Tool

Supporting real time video transmission over wireless networks is very challenging. The video flow characteristics can be vulnerable to the time-varying channel conditions and the unreliability of the MAC (Medium Access Control) can substantially degrade Quality of Experience (QoE) in wireless networks. QoE reflects the satisfaction level of a user towards a particular service or application. It can be a valuable input to service providers and help them to enhance the quality of the overall system. In this work, we present a methodology and a system based on Random Neural Network (RNN) to analyze the impact of different MAC-level parameters on video QoE over IEEE 802.11n wireless networks. At first, subjective tests are performed to correlate MAC-level parameters with user's perceived video QoE. Secondly, we propose a RNN technique to estimate the impact of these parameters on video QoE. The experimental results show that the proposed method can effectively measure the impact of MAC-level parameters on video QoE. The acceptable correlation between subjective QoE and estimated QoE verifies the validity of the obtained results.

Bachar Wehbi

Papers

Estimation of QoE of video traffic using a fuzzy expert system

Timed Extended Invariants for the Passive Testing of Web Services

Events-Based Security Monitoring Using MMT Tool

Estimation of video QoE from MAC parameters in wireless network: A Random Neural Network approach

Address Autoconfiguration in Ad Hoc Networks