MIPv6 Experimental Evaluation using Overlay Networks

The commercial deployment of Mobile IPv6 has been hastened by the concepts of Integrated Wireless Networks and Overlay Networks, which are present in the notion of the forthcoming generation of wireless communications. Individual wireless access networks show limitations that can be overcome through the integration of different technologies into a single unified platform (i.e., 4G systems). This paper summarises practical experiments performed to evaluate the impact of inter-networking (i.e. vertical handovers) on the Network and Transport layers. Based on our observations, we propose and evaluate a number of inter-technology handover optimisation techniques, e.g., Router Advertisements frequency values, Binding Update simulcasting, Router Advertisement caching, and Soft Handovers. The paper concludes with the description of a policy-based mobility support middleware (PROTON) that hides 4G networking complexities from mobile users, provides informed handover-related decisions, and enables the application of different vertical handover methods and optimisations according to context.Publicad

Learning and Reasoning Strategies for User Association in Ultra-dense Small Cell Vehicular Networks

Recent vehicular ad hoc networks research has been focusing on providing intelligent transportation services by employing information and communication technologies on road transport. It has been understood that advanced demands such as reliable connectivity, high user throughput, and ultra-low latency required by these services cannot be met using traditional communication technologies. Consequently, this thesis reports on the application of artificial intelligence to user association as a technology enabler in ultra-dense small cell vehicular networks. In particular, the work focuses on mitigating mobility-related concerns and networking issues at different mobility levels by employing diverse heuristic as well as reinforcement learning (RL) methods. Firstly, driven by rapid fluctuations in the network topology and the radio environment, a conventional, three-step sequence user association policy is designed to highlight and explore the impact of vehicle speed and different performance indicators on network quality of service (QoS) and user experience. Secondly, inspired by control-theoretic models and dynamic programming, a real-time controlled feedback user association approach is proposed. The algorithm adapts to the changing vehicular environment by employing derived network performance information as a heuristic, resulting in improved network performance. Thirdly, a sequence of novel RL based user association algorithms are developed that employ variable learning rate, variable rewards function and adaptation of the control feedback framework to improve the initial and steady-state learning performance. Furthermore, to accelerate the learning process and enhance the adaptability and robustness of the developed RL algorithms, heuristically accelerated RL and case-based transfer learning methods are employed. A comprehensive, two-tier, event-based, system level simulator which is an integration of a dynamic vehicular network, a highway, and an ultra-dense small cell network is developed. The model has enabled the analysis of user mobility effects on the network performance across different mobility levels as well as served as a firm foundation for the evaluation of the empirical properties of the investigated approaches

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover

A Study of Mobility Support in Wearable Health Monitoring Systems: Design Framework

International audienceThe aim of this work is to investigate main techniques and technologies enabling user's mobility in wearable health monitoring systems. For this, design requirements for key enabling mechanisms are pointed out, and a number of conceptual and technological recommendations are presented. The whole is schematized and presented into the form of a design framework covering design layers and taking in consideration patient context constraints. This work aspires to bring a further contribution for the conception and possibly the evaluation of health monitoring systems with full support of mobility offering freedom to users while enhancing their life qualit

Immersive interconnected virtual and augmented reality : a 5G and IoT perspective

Despite remarkable advances, current augmented and virtual reality (AR/VR) applications are a largely individual and local experience. Interconnected AR/VR, where participants can virtually interact across vast distances, remains a distant dream. The great barrier that stands between current technology and such applications is the stringent end-to-end latency requirement, which should not exceed 20 ms in order to avoid motion sickness and other discomforts. Bringing AR/VR to the next level to enable immersive interconnected AR/VR will require significant advances towards 5G ultra-reliable low-latency communication (URLLC) and a Tactile Internet of Things (IoT). In this article, we articulate the technical challenges to enable a future AR/VR end-to-end architecture, that combines 5G URLLC and Tactile IoT technology to support this next generation of interconnected AR/VR applications. Through the use of IoT sensors and actuators, AR/VR applications will be aware of the environmental and user context, supporting human-centric adaptations of the application logic, and lifelike interactions with the virtual environment. We present potential use cases and the required technological building blocks. For each of them, we delve into the current state of the art and challenges that need to be addressed before the dream of remote AR/VR interaction can become reality

Modeling Seamless Vertical Handovers in Heterogeneous Wireless Networks

Vertical handover in heterogeneous wireless networks provides customers with better Quality of Service (QoS) experience. For seamless handover, timely initiation of handover process plays a key role. Various vertical handover management protocols have been proposed and standardized to support mobility across heterogeneous networks. In Media Independent Handover (MIH) based schemes, distributed handover decision is made via certain predefined triggers that consider user context. In this paper, we present a comprehensive review of the modeling techniques used during management of vertical handover. We have also defined a novel architecture, HRPNS: Handoff Resolving and Preferred Network Selection module enabling vertical handover that ensures QoS. The construction of HRPNS module involves integration of fuzzy logic and Markov Decision Process (MDP) for providing precise decision of handover