Objective
SMEs and public sector organizations increasingly investigate the possibilities to use cloud computing services in their everyday business conduct. Accessing services and resources in the cloud on-demand and in a flexible and elastic way could result in significant cost savings due to more efficient and convenient resource utilization that also replaces large investment costs with long term operational costs. On the other hand, the take up of cloud computing by SMEs and the public sector is still relatively low due to limited application-level flexibility and also security concerns. The Cloud Orchestration at the Level of Application (COLA) project aims to increase the adoption of cloud computing services by the above mentioned two strategic target communities. Typical industry and public sector applications require resource scalability and efficient resource utilization in order to serve a variable number of customers with dynamic resource demands, and to suitably optimize resource consumption and costs. However, the dynamic and intelligent utilization of cloud infrastructure resources from the perspective of cloud applications is not trivial. Although there have been several efforts to support the intelligent and coordinated deployment, and to a smaller extent also the run-time orchestration of cloud applications, no comprehensive solution has emerged until now that could be applied in large scale near operational level industry trials. The overall objective of the COLA project is that by building on and extending current research results, it will define and provide a reference implementation of a generic and pluggable framework that supports the optimal and secure deployment and run-time orchestration of cloud applications. COLA will demonstrate the applicability and impact of the solution via large scale near operational level SME and public sector pilots and demonstrators, and will also define a clear pathway how the innovation can be delivered to the market.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
Programme(s)
Topic(s)
Funding Scheme
IA - Innovation actionCoordinator
W1B 2UW London
United Kingdom
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Participants (16)
1111 Budapest
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8005 Zurich
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
8808 PFAFFIKON SZ
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participation ended
164 29 Kista
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8048 Zurich
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
Participation ended
1117 BUDAPEST
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50197 Zaragoza
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50018 Zaragoza
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Participation ended
EC2M 4LX LONDON
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UB8 3PH Uxbridge
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B96 6PL ASTWOOD BANK WORCESTERSHIRE
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
N4 3JU London
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
47057 Duisburg
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
M4 1LE Manchester
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
1117 BUDAPEST
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501 15 Boras
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