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Titlebook: Autonomous Control for a Reliable Internet of Services; Methods, Models, App Ivan Ganchev,R. D. van der Mei,Hans van den Berg Book‘‘‘‘‘‘‘‘

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楼主: Julienne
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Aesthetic Discrimination of Graph LayoutsFV with QoS-aware service composition, ranging from the energy efficient placement of virtual network functions inside modern data centers, to the deployment of data stream processing applications using SDN to control the network paths, to exploiting SDN for context-aware service compositions.
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Context Monitoring for Improved System Performance and QoE, benefits of including context in QoE monitoring and management are demonstrated through use cases involving video flash crowds as well as online and cloud gaming..Finally, we discuss potential technical realizations of context-aware QoE monitoring and management derived based on the SDN paradigm.
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0302-9743 OST Action IC1304 “Autonomous Control for a Reliable Internet of Services (ACROSS)”. The book contains 14 chapters and constitutes a show-case of the main outcome of the Action in line with its scientific goals. It will serve as a valuable reference for undergraduate and post-graduate students, educ
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https://doi.org/10.1007/BFb0021783cost/quality ratios are proposed – mean and instantaneous – along with illustrative numerical predictions of the latter, which could be useful for dynamic pricing policy execution, depending on the network load. All defined indicators could be considered as sources for Quality of Experience (QoE) prediction.
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Stina Bridgeman,Roberto Tamassiat-aware strategy manages to successfully mitigate stallings in light of network connectivity problems, such as an outage. Moreover, we analyze the performance of this strategy by comparing it to the optimal case, as well as by considering situations where the awareness of the context lacks reliability.
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,Scalable Traffic Quality and System Efficiency Indicators Towards Overall Telecommunication System’cost/quality ratios are proposed – mean and instantaneous – along with illustrative numerical predictions of the latter, which could be useful for dynamic pricing policy execution, depending on the network load. All defined indicators could be considered as sources for Quality of Experience (QoE) prediction.
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