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A software workbench for interactive, time critical and highly self-adaptive cloud applications (SWITCH)

Zhao, Zhiming, Taal, Arie, Jones, Andrew Clifford, Taylor, Ian James, Stankovski, Vlado, Vega, Ignacio Garcia, Hidalgo, Francisco Jesus, Suciu, George, Ulisses, Alexandre, Ferreira, Pedro and Laat, Cees de 2015. A software workbench for interactive, time critical and highly self-adaptive cloud applications (SWITCH). Presented at: 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), Shenzhen, China, 4-7 May 2015. Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on. IEEE, pp. 1181-1184. 10.1109/CCGrid.2015.73

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Abstract

Time critical applications have very high requirements on network and computing services, in particular on well-tuned software architecture with sophisticated optimisation on data communication. Their development is often customised to dedicated infrastructure, and system performance is difficult to maintain when infrastructure changes. This fatal weakness in existing architecture and software tools causes very high development costs, and makes it difficult to fully utilise the virtualised, programmable and quality-on-demand services provided by networked Clouds to improve the system productivity. The Software Workbench for Interactive, Time Critical and Highly self-adaptive Cloud applications (SWITCH) is a newly funded project by EU H2020 to address this urgent industrial need, it aims at improving the existing development and execution model of time critical applications by introducing a novel conceptual model called application-infrastructure co-programming and control model, in which application QoS/QoE together with the programmability and controllability of Cloud environments can be all included in the complete lifecycle of applications.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Publisher: IEEE
Funders: EC (Horizon 2020)
Last Modified: 15 Dec 2017 11:47
URI: http://orca.cf.ac.uk/id/eprint/84845

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