189 research outputs found

    Survey of Transportation of Adaptive Multimedia Streaming service in Internet

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    [DE] World Wide Web is the greatest boon towards the technological advancement of modern era. Using the benefits of Internet globally, anywhere and anytime, users can avail the benefits of accessing live and on demand video services. The streaming media systems such as YouTube, Netflix, and Apple Music are reining the multimedia world with frequent popularity among users. A key concern of quality perceived for video streaming applications over Internet is the Quality of Experience (QoE) that users go through. Due to changing network conditions, bit rate and initial delay and the multimedia file freezes or provide poor video quality to the end users, researchers across industry and academia are explored HTTP Adaptive Streaming (HAS), which split the video content into multiple segments and offer the clients at varying qualities. The video player at the client side plays a vital role in buffer management and choosing the appropriate bit rate for each such segment of video to be transmitted. A higher bit rate transmitted video pauses in between whereas, a lower bit rate video lacks in quality, requiring a tradeoff between them. The need of the hour was to adaptively varying the bit rate and video quality to match the transmission media conditions. Further, The main aim of this paper is to give an overview on the state of the art HAS techniques across multimedia and networking domains. A detailed survey was conducted to analyze challenges and solutions in adaptive streaming algorithms, QoE, network protocols, buffering and etc. It also focuses on various challenges on QoE influence factors in a fluctuating network condition, which are often ignored in present HAS methodologies. Furthermore, this survey will enable network and multimedia researchers a fair amount of understanding about the latest happenings of adaptive streaming and the necessary improvements that can be incorporated in future developments.Abdullah, MTA.; Lloret, J.; Canovas Solbes, A.; GarcĂ­a-GarcĂ­a, L. (2017). Survey of Transportation of Adaptive Multimedia Streaming service in Internet. Network Protocols and Algorithms. 9(1-2):85-125. doi:10.5296/npa.v9i1-2.12412S8512591-

    Towards Intelligent Energy-Aware Self-Organised Cellular Networks (iSONs)

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    This thesis investigates the application of intelligent energy-aware resource management techniques for current and future wireless broadband deployments. Energy-aware topology management is firstly studied aiming at dynamically managing the network topology by fine tuning the status of network entities (dormant / active) to scale the energy consumption with traffic demands. This is studied through an analytical model based on queueing theory and through simulation to help understand its operational capabilities under a range of traffic conditions. Advanced radio resource management is also investigated. This reduces the number of nodes engaged in the service whenever possible reducing the energy consumption at low and medium traffic loads while enhancing system capacity and QoS when the traffic load is high. As an enabling technology for self-awareness and adaptability, Reinforcement Learning (RL) is applied to manage network resources in an intelligent, self-aware, and adaptable manner. This is complemented with a range of novel cognitive learning and reasoning algorithms which are capable of translating past experience into valuable sets of information in order to optimise decisions taken as part of the radio resource and topology management functionalities. Dependencies between the proposed techniques are also addressed formulating an intelligent self-adaptable approach, which is capable of dynamically deactivating redundant nodes and redirecting traffic appropriately while enhancing system capacity and QoS

    Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

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    This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

    On the efficiency of dynamic licensed shared access for 5G/6G wireless communications

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    The licensed shared access (LSA) is a spectrum licensing scheme authorizing additional new users (the licensees) to dynamically share the same spectrum with the old users (the incumbents). Contained in the terms of the spectrum usage authorization is a set of strict protective measures for the incumbent system which introduce extra restrictions on the licensee operations. Such measures imply that the licensee’s access to the spectrum can be revoked or restricted at any time which may result in the degradation of critical performance metrics of the latter. Addressing this issue and the accompanying challenges as we enter the 5G zettabytes era motivates the research problems addressed in this thesis. A vertical LSA spectrum sharing involving a mobile network operator (MNO) as the licensee and two categories of incumbent including the aeronautical telemetry, and a group of terrestrial public and ancillary wireless services is adopted in this thesis. Firstly, an analytical examination of the uplink and downlink licensee’s transmit power, when its spectrum access right is revoked (i.e., the limited transmit power) is done. Then a power allocation scheme that maximizes the energy efficiency (EE) of the licensee when it is operating with limited transmit power is proposed. Simulation results reveal the impact of the LSA spectrum access revocation on the allowable transmit power of the licensee as a function of the effect of different interference propagation path and the transmission direction. A comparison of the proposed optimal power allocation method with the equal power allocation (EPA) method further shows considerable improvement in the achievable EE of the licensee. Furthermore, in the LSA, the achievable spectrum efficiency (SE) of the licensee is limited by the interference threshold constraint set by the incumbent’s protective measures. Consequent on this, we propose an SE maximization of the licensee’s system subject to the incumbent interference threshold constraint. Furthermore, the LSA band spectral utilization was characterised as a function of the licensee’s achievable SE and the statistics of the LSA spectrum availability. The obtained results provide quantitative insights for practical system design and deployment of the LSA system, especially when compared to the results obtained in the maximization of the EE. In particular, the effect of variations in critical operational parameters throws up interesting network design trade-off challenge, worthy of consideration. This informs the subsequent multi objective optimization of the EE-SE trade-off investigated next. Interestingly, the obtained results indicate that with careful selection of the licensee eNodeB coverage radius, transmit power, and number of user equipment per eNodeB coverage area, one can engineer the best possible trade-off between the spectrum and energy efficiency in practical LSA deployment. A major LSA feature is guaranteeing predictable quality of service (QoS) for both the incumbent and the licensee systems. In terrestrial implementation, the reduction in the achievable data rate caused by the incumbents’ protective measures, may violate guaranteed QoS in the licensee system. To address this issue, we propose a LSA - based hybrid aerialterrestrial system with drone base station (D-BS). Simulation results show that using the proposed scheme, the licensee, when operating under the incumbents’ imposed restrictions, is able to achieve the QoS data rate requirements of the users on its network. In conclusion, the findings in this research indicates that the dynamic LSA is a practically viable solution to the spectrum management requirements of the emerging vertical wireless technologies in 5G and beyond
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