When a single Cloud service (i.e., a software
image and a virtual machine), on its own, cannot satisfy all the user
requirements, a composition of Cloud services is required. Cloud service
composition, which includes several tasks such as discovery, compatibility
checking, selection, and deployment, is a complex process and users find it
difficult to select the best one among the hundreds, if not thousands, of
possible compositions available. Service composition in Cloud raises even new
challenges caused by diversity of users with different expertise requiring
their applications to be deployed across difference geographical locations with
distinct legal constraints. The main difficulty lies in selecting a combination
of virtual appliances (software images) and infrastructure services that are
compatible and satisfy a user with vague preferences. Therefore, we present a
framework and algorithms which simplify Cloud service composition for unskilled
users. We develop an ontology based approach to analyze Cloud service
compatibility by applying reasoning on the expert knowledge. In addition, to
minimize effort of users in expressing their preferences, we apply combination
of evolutionary algorithms and fuzzy logic for composition optimization. This
lets users express their needs in linguistics terms which brings a great
comfort to them compared to systems that force users to assign exact weights
for all preferences
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