The cloud is an outstanding
platform to deal with functionally equivalent services which are exponentially
increasing day-by-day. The selection of services
to meet the client requirements is a subtle task. The services can be selected by
ranking all the candidate services using their network and non-network Quality-of-Service (QoS) parameters, which is formulated as a NP hard optimization problem. In this paper, we
proposed a linear discriminant analysis (LDA) based a four level matching model for service selection based on QoS parameters,
which includes description matching of a service, matchmaking phase, LDA-based QoS matching and ranking. The LDA-service
selection agent is deployed on each cloud to classify services into classes and
rank the services based on the aggregate QoS value of each service. Finally,
the test results show the efficiency in service selection with minimal
discovery overhead, significant reduction in the computation time and the
number of candidate services to be considered.
