Model integration method and supporting tooling: project deliverable D5.1

Medientyp: Bericht; E-Book

Titel: Model integration method and supporting tooling: project deliverable D5.1

Beteiligte: Groenda, Henning [VerfasserIn]; Stier, Christian [VerfasserIn]; Krzywda, Jakub [VerfasserIn]; Byrne, James [VerfasserIn]; Svorobej, Sergej [VerfasserIn]; Papazachos, Zafeirios [VerfasserIn]; Sheridan, Craig [VerfasserIn]; Whigham, Darren [VerfasserIn]; Östberg, Per-Olov [VerfasserIn]

Erschienen: Universität Ulm, 2017-04-21T09:47:54Z

Sprache: Englisch

DOI: https://doi.org/10.18725/OPARU-4317

Schlagwörter: Electric network topology ; DDC 004 / Data processing & computer science ; Datenmanagement ; Analytics ; Cloud ; Cloud services ; Model integration ; Tooling ; Context-aware cloud topology ; Data management ; Cactos Projekt ; Cloud computing

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Beschreibung: The CACTOS project aims to improve the operational efficiency of cloud data centres by supporting data centre operators in the planning and operation of heterogeneous data centres. One major goal of CACTOS is to enable automated capacity and resource management for virtualised infrastructure environments built upon the Infrastructure as a Service (IaaS) paradigm. This document outlines the model‐driven methodology developed for the integration of runtime monitoring of cloud‐based data centres with runtime optimisation techniques. The CACTOS project develops an integrated solution for runtime monitoring, optimisation and predictive analysis of data centres. The solution supports data centre providers in managing and planning data centres. CACTOS consists of two toolkits: • The CACTOS Runtime Toolkit enables automated resource planning and optimisation for IaaS data centres. • The CACTOS Prediction Toolkit supports what‐if analyses for existing or planned data centre topologies that account for effects caused by automated resource optimisation. While the focus of this document is to describe the integration methodology developed to couple runtime monitoring and optimisation for cloud data centres in the CACTOS Runtime Toolkit, the outlined methodology was developed to facilitate the integration across all toolkits developed in CACTOS. Hence, the integration of optimisation and monitoring with the simulative predictions in the CACTOS Prediction Toolkit is also discussed. The main contributions of this deliverable are the CACTOS Cloud Infrastructure Models that define the common language through which the runtime analytics tool, CactoScale, and the optimisation tool, CactoOpt, exchange information on the data centre’s structure and operational state. The models allow for the capturing of the deployment of Virtual Machines (VMs) on the middleware used in cloud data centres. Additionally, they track measurements and metrics that reflect the operational efficiency of the data centre. Instances of the CACTOS Cloud ...

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