6,805 research outputs found

    Overlay networks for smart grids

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    Approaches for Future Internet architecture design and Quality of Experience (QoE) Control

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    Researching a Future Internet capable of overcoming the current Internet limitations is a strategic investment. In this respect, this paper presents some concepts that can contribute to provide some guidelines to overcome the above-mentioned limitations. In the authors' vision, a key Future Internet target is to allow applications to transparently, efficiently and flexibly exploit the available network resources with the aim to match the users' expectations. Such expectations could be expressed in terms of a properly defined Quality of Experience (QoE). In this respect, this paper provides some approaches for coping with the QoE provision problem

    QoE for Mobile Streaming

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    Multimedia Streaming through Wireless Networks

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    An overview of wireless networks, cross-layer optimization techniques, and advances in wireless LAN technologies is presented. This paper presents a scalable and adaptive system-level approach to wireless multimedia in the emerging, Proactive Enterprise computing environment. A Distributed Network Information Base with Service Agents at each node is proposed to enable network-wide, proactive adaptation with adaptive routing and end-to-end Quality of Service (QoS) management. The paper suggests that a combination of technological advancements in emerging wireless networks, node-level cross-layer optimizations, and the proposed distributed cross-node system-level architecture are all required to efficiently scale and adapt wireless multimedia in the current market

    Cross-layer Scheduling with Feedback for QoS Support

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    AbstractNext-Generation Networks (NGNs) will support Quality of Service (QoS) over a mixed wired and wireless IP-based infrastructure. A relative model of service differentiation in Differentiated Services architecture is a scalable solution for delivering multimedia traffic. However, considering the dynamic nature of radio channels typically, it is difficult to achieve a given service provisioning working at the IP and lower layers separately as in the classical approach, without a run-time adaptation of the system towards the target quality. This work describes an IP cross-layer scheduler able to support a Proportional Differentiation Model (PDM) for delay guarantees with content-awareness, also over wireless. The key idea is to leverage feedbacks from the lower layers about the actual delays experienced by packets in order to tune at run-time the priority of the IP service classes in a closed-loop control with the objective of supporting a PDM at the network node on the whole, considering the cumulative latency in crossing the first three layers of the protocol stack, as relevant for the end-user. A simulation analysis demonstrates the prominent improvements in reliability and robustness of the proposal in the case of time-variant performance of the MAC and PHY layers with respect to the classical non-cross-layer approach and the open- loop control. Furthermore, considerations on the required functionality and likely deployment scenarios highlight the scalability and backward compatibility of the designed solution in supporting the concept of network transparency for the delivering of critical applications, as of the e-health domain

    Orchestrating Service Migration for Low Power MEC-Enabled IoT Devices

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    Multi-Access Edge Computing (MEC) is a key enabling technology for Fifth Generation (5G) mobile networks. MEC facilitates distributed cloud computing capabilities and information technology service environment for applications and services at the edges of mobile networks. This architectural modification serves to reduce congestion, latency, and improve the performance of such edge colocated applications and devices. In this paper, we demonstrate how reactive service migration can be orchestrated for low-power MEC-enabled Internet of Things (IoT) devices. Here, we use open-source Kubernetes as container orchestration system. Our demo is based on traditional client-server system from user equipment (UE) over Long Term Evolution (LTE) to the MEC server. As the use case scenario, we post-process live video received over web real-time communication (WebRTC). Next, we integrate orchestration by Kubernetes with S1 handovers, demonstrating MEC-based software defined network (SDN). Now, edge applications may reactively follow the UE within the radio access network (RAN), expediting low-latency. The collected data is used to analyze the benefits of the low-power MEC-enabled IoT device scheme, in which end-to-end (E2E) latency and power requirements of the UE are improved. We further discuss the challenges of implementing such schemes and future research directions therein

    Ethernet - a survey on its fields of application

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    During the last decades, Ethernet progressively became the most widely used local area networking (LAN) technology. Apart from LAN installations, Ethernet became also attractive for many other fields of application, ranging from industry to avionics, telecommunication, and multimedia. The expanded application of this technology is mainly due to its significant assets like reduced cost, backward-compatibility, flexibility, and expandability. However, this new trend raises some problems concerning the services of the protocol and the requirements for each application. Therefore, specific adaptations prove essential to integrate this communication technology in each field of application. Our primary objective is to show how Ethernet has been enhanced to comply with the specific requirements of several application fields, particularly in transport, embedded and multimedia contexts. The paper first describes the common Ethernet LAN technology and highlights its main features. It reviews the most important specific Ethernet versions with respect to each application field’s requirements. Finally, we compare these different fields of application and we particularly focus on the fundamental concepts and the quality of service capabilities of each proposal
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