Modeling and performance analysis of an alternative to IEEE 802.11e Hybrid Control Function

Modern wireless networks are offering a wide range of applications that require the efficient integration of multimedia and traditional data traffic along with QoS provision. The IEEE 802.11e workgroup has standardized a new QoS enhanced access scheme for wireless LANs, namely Hybrid Control Function (HCF). HCF consists of the Enhanced Distributed Channel Access (EDCA) and the Hybrid Control Channel Access (HCCA) protocols which manage to ensure QoS support. However, they exhibit specific weaknesses that limit network performance. This work analyzes an alternative protocol, called Priority Oriented Adaptive Polling (POAP). POAP is an integrated channel access mechanism, is collision free, it employs priorities to differentiate traffic in a proportional way, it provides fairness, and generally supports QoS for all types of multimedia applications, while efficiently serving background data traffic. POAP is compared to HCF in order to examine the wireless network performance when serving integrated traffic

Mobile crowd sensing architectural frameworks: A comprehensive survey

Mobile Crowd Sensing has emerged as a new sensing paradigm, efficiently exploiting human intelligence and mobility in conjunction with advanced capabilities and proliferation of mobile devices. In order for MCS applications to reach their full potentials, a number of research challenges should be sufficiently addressed. The aim of this paper is to survey representative mobile crowd sensing applications and frameworks proposed in related research literature, analyze their distinct features and discuss on their relative merits and weaknesses, highlighting also potential solutions, in order to take a step closer to the definition of a unified MCS architectural framework

The Hunter: Tracking Randomly Moving WBAN Targets

Wireless Sensor Networks are often large networks comprised of nodes that monitor through sensors interesting targets. Wireless Body Area Networks are always small networks that often monitor the health of a single human subject. Although WBANs are limited in size, the information they monitor is urgent and important. Information from a WBAN producer may be transmitted over a WSN to the intended consumer

The Hunter: Tracking Randomly Moving WBAN Targets

Wireless Sensor Networks are often large networks comprised of nodes that monitor through sensors interesting targets. Wireless Body Area Networks are always small networks that often monitor the health of a single human subject. Although WBANs are limited in size, the information they monitor is urgent and important. Information from a WBAN producer may be transmitted over a WSN to the intended consumer

Detection of Physical Adversarial Attacks on Traffic Signs for Autonomous Vehicles

Current vision-based detection models within Autonomous Vehicles, can be susceptible to changes within the physical environment, which cause unexpected issues. Physical attacks on traffic signs could be malicious or naturally occurring, causing incorrect identification of the traffic sign which can drastically alter the behaviour of the autonomous vehicle. We propose two novel deep learning architectures which can be used as detection and mitigation strategy for environmental attacks. The first is an autoencoder which detects anomalies within a given traffic sign, and the second is a reconstruction model which generates a clean traffic sign without any anomalies. As the anomaly detection model has been trained on normal images, any abnormalities will provide a high reconstruction error value, indicating an abnormal traffic sign. The reconstruction model is a Generative Adversarial Network (GAN) and consists of two networks; a generator and a discriminator. These map the input traffic sign image into a meta representation as the output. By using anomaly detection and reconstruction models as mitigation strategies, we show that the performance of the other models in pipelines such as traffic sign recognition models can be significantly improved. In order to evaluate our models, several types of attack circumstances were designed and on average, the anomaly detection model achieved 0.84 accuracy with a 0.82 F1-score in real datasets whereas the reconstruction model improved performance of traffic sign recognition model from average F1-score 0.41 to 0.641

Multi-Stage Resource Allocation in Hybrid 25G-EPON and LTE-Advanced Pro FiWi Networks for 5G Systems

The 5G vision is not restricted solely to the wireless domain and its challenging requirements cannot be fulfilled with- out the efficient integration of cutting-edge technologies in all portions of the telecommunications infrastructure. The promoted architectures for next generation telecommunications systems involve high capacity network domains, which operate flexibly and seamlessly to offer full Quality of Experience to all types of subscribers. The proliferation of highly demanding multimedia services and the advanced features of modern communication devices necessitate the development of end-to-end schemes which can efficiently distribute large amount of network resources anywhere and whenever needed. The paper introduces a new resource allocation scheme for cutting-edge Fiber-Wireless networks is introduced that can be applied in the fronthaul portion of 5G-enabled architectures. The adopted technologies are the forthcoming 25G-EPON for the optical domain and the 5G-ready LTE-Advanced Pro for the wireless domain. The proposed scheme performs allocation decisions based on the outcome of an adjustable multi- stage optimization problem. The optimization factors are directly related to the major considerations in bandwidth distribution, namely priority-based traffic differentiation, power awareness, and fairness provision. The conducted evaluations prove that this approach is able to ensure high efficiency in network operations

Exploring the intra-frame energy conservation capabilities of the horizontal simple packing algorithm in IEEE 802.16e networks: an analytical approach

The power saving capabilities of the mobile devices in broadband wireless networks constitute a challenging research topic that has attracted the attention of researchers recently, while it needs to be addressed at multiple layers. This work provides a novel analysis of the intra-frame energy conservation potentials of the IEEE 802.16e network. Specifically, the power saving capabilities of the worldwide interoperability for microwave access downlink sub-frame are thoroughly studied, employing the well-known simple packing algorithm as the mapping technique of the data requests. The accurate mathematical model, cross-validated via simulation, reveals the significant ability to conserve energy in this intra-frame fashion under different scenarios. To the best of our knowledge, this is the first work providing intra-frame power-saving potentials of IEEE 802.16 networks. Additionally, this is the first study following an analytic approach

A Novel Method of Serving Multimedia and Background Traffic in Wireless LANs.

Wireless local area networks (LANs) require the efficient integration of multimedia and traditional data traffic. This paper proposes the priority-oriented adaptive polling (POAP) protocol that could be used in place of the enhanced distributed channel access (EDCA) part of the IEEE 802.11e access scheme. EDCA seems capable of differentiating traffic; however, it exhibits great overhead that limits the available bandwidth and degrades performance. POAP is collision free, prioritizes the different kinds of traffic, and is able to provide quality of service (QoS) for all types of multimedia network applications while efficiently supporting background data traffic. POAP, compared to EDCA, provides higher channel utilization, distributes resources to the stations adapting to their real needs, and generally exhibits superior performance

Feasibility of sensor-based technology for monitoring health in developing countries - cost analysis and user perception aspects

Understanding the financial burden of chronic diseases in developing regions still remains an important economical factor which influences the successful implementation of sensor based applications for continuous monitoring of chronic conditions. Our research focused on a comparison of literature-based data with real costs of the management and treatment of chronic diseases in a developing country, and we are using Kosovo as an example here. The results reveal that the actual living costs exceed the minimum expenses that chronic diseases impose. Following the potential of a positive economic impact of sensor based platforms for monitoring chronic conditions, we further examined the users perception of digital technology. The purpose of this paper is to present the varying cost levels of treating chronic diseases, identify the users concerns and requirements towards digital technology and discuss issues and challenges that the application of sensor based platforms imply in low and middle income countries

Predicting Multimedia Traffic in Wireless Networks: A Performance Evaluation of Cognitive Techniques

Traffic engineering in networking is defined as the process that incorporates sophisticated methods in order to ensure optimization and high network performance. One of the most constructive tools employed by the traffic engineering concept is the traffic prediction. Having in mind the heterogeneous traffic patterns originated by various modern services and network platforms, the need of a robust, cognitive, and error-free prediction technique becomes even more pressing. This work focuses on the prediction concept as an autonomous, functional, and efficient process, where multiple cutting-edge methods are presented, modeled, and thoroughly assessed. To this purpose, real traffic traces have been captured, including multiple multimedia traffic flows, so as to comparatively assess widely used methods in terms of accuracy