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Energy vs. QoX network- and cloud services management
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A3 Kirjan tai muun kokoomateoksen osa
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en
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28
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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) ; Volume LNCS 10768
Abstract
Network Performance (NP)- and more recently Quality of Service/Experience/anything (QoS/QoE/QoX)-based network management techniques focus on the maximization of associated Key Performance Indicators (KPIs). Such mechanisms are usually constrained by certain thresholds of other system design parameters. e.g., typically, cost. When applied to the current competitive heterogeneous Cloud Services scenario, this approach may have become obsolete due to its static nature. In fact, energy awareness and the capability of modern technologies to deliver multimedia content at different possible combinations of quality (and prize) demand a complex optimization framework. It is therefore necessary to define more flexible paradigms that make it possible to consider cost, energy and even other currently unforeseen design parameters not as simple constraints, but as tunable variables that play a role in the adaptation mechanisms. In this chapter we will briefly introduce most commonly used frameworks for multi-criteria optimization and evaluate them in different Energy vs. QoX sample scenarios. Finally, the current status of related network management tools will be described, so as to identify possible application areas.
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Blanco, B, Liberal, F, Lassila, P, Aalto, S, Sainz, J, Gribaudo, M & Pernici, B 2018, Energy vs. QoX network- and cloud services management. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. LNCS 10768, Springer, pp. 241-268. https://doi.org/10.1007/978-3-319-90415-3_10