2,467 research outputs found

    Scalable monitoring and optimization techniques for mega-scale data centers

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    Network streaming and compression for mixed reality tele-immersion

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    Bulterman, D.C.A. [Promotor]Cesar, P.S. [Copromotor

    Networking - A Statistical Physics Perspective

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    Efficient networking has a substantial economic and societal impact in a broad range of areas including transportation systems, wired and wireless communications and a range of Internet applications. As transportation and communication networks become increasingly more complex, the ever increasing demand for congestion control, higher traffic capacity, quality of service, robustness and reduced energy consumption require new tools and methods to meet these conflicting requirements. The new methodology should serve for gaining better understanding of the properties of networking systems at the macroscopic level, as well as for the development of new principled optimization and management algorithms at the microscopic level. Methods of statistical physics seem best placed to provide new approaches as they have been developed specifically to deal with non-linear large scale systems. This paper aims at presenting an overview of tools and methods that have been developed within the statistical physics community and that can be readily applied to address the emerging problems in networking. These include diffusion processes, methods from disordered systems and polymer physics, probabilistic inference, which have direct relevance to network routing, file and frequency distribution, the exploration of network structures and vulnerability, and various other practical networking applications.Comment: (Review article) 71 pages, 14 figure

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

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    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

    ON INTEGRATION OF EVOLVING INFRASTRUCTURE TOPOLOGY GRAPHS AND METRIC DATA STREAMS IN INFORMATION TECHNOLOGY INFRASTRUCTURE MANAGEMENT

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    Modern cloud-based information technology (IT) infrastructure monitoring context and data are gathered from various systems. Typical monitoring systems provide a set of metrics characterizing the performance and health of a variety of infrastructure components. To understand the dependencies and relations among these measurements, the infrastructure topology can be analysed to provide context to the monitoring metrics. However, the metrics and the topology are updated at different time intervals and providing continuous merging and analysis of both data sets is a challenging task which is rarely addressed in the scientific literature. The paper elaborates a method for integration of infrastructure topology graph and monitoring metric data streams. The method is intended for application in the identification of anomalies in IT infrastructure.
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