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2 Cloud Computing management
Table I.8 – Data placement policies for data-intensive applications in the inter-cloud environment
Title Data placement policies for data-intensive applications in the inter-cloud
environment
Description Data-intensive applications are widely used in an increasing number of fields,
e.g., high-energy physics, bioinformatics and astronomy. There are several
challenges if the datasets required by this kind of application, including already
existing data, intermediate data and final data, should be placed in the inter-
cloud environment. Therefore, it is essential for federated CSPs to negotiate an
appropriate placement policy for the different datasets. The placement policy
conditions include, but are not limited to, the time cost of data transmission,
storage space, network performance and data dependencies. The following
aspects are described as the illustrations.
– The transmission of data among different CSPs is inevitable. On one hand,
the data scale is huge and the bandwidth limited; on the other, sometimes,
there are several datasets limited to location in some specific CSP based on
application logic. Consideration of how to reduce the time cost of data
movements is required.
– There are dependencies among these different datasets placed in different
CSPs. Consideration of how to maintain these dependencies is required in
order to improve calculation efficiency.
Roles CSC, CSP (SaaS), CSP (NaaS, SaaS)
Figure (optional)
Pre-conditions (optional) The CSPs form an inter-cloud federation pattern.
The datasets need placement in different CSPs.
There are dependencies among these datasets.
Post-conditions (optional)
Derived requirements Dataset placement policies among different CSPs (see clause 8.1)
I.9 Use case of data regulation across different countries in the inter-cloud environment
This use case illustrates data regulation across different countries in the inter-cloud. The inter-cloud peering
pattern used to illustrate the use case is an example only.
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