To provide on-demand Cloud services, Cloud
providers and customers are used to sign Service Level
Agreement (SLA), which is an agreement on the level of service
provided and its associated cost. Unfortunately, SLA is not as
dynamic as the Cloud and the criteria on which a customer relies
to select a provider can be of problematic nature. The provider
must optimize its resources although he cannot predict the
customer behavior that can make varying requests. This can have
a direct impact on the availability of resources and thus may lead
to SLA violations. To cope with this issue, we propose a
framework that allows the customer to choose a trusted provider
based on its reputation calculated using a Bayesian network and
continuously updated via a Cloud directory. Moreover, we
propose a smart and dynamic SLA scheme that uses a
probabilistic ontology capable of detecting potential violations of
contract parameters; in addition, it alerts the service provider
about these violations. To evaluate our model we used data
extracted from Amazon Web Service Elastic Cloud Compute and
Google Compute Engine SLAs to simulate our proposal s
environment. The results of our experiments show the
effectiveness of probabilistic ontology for predicting SLA
violation throughout some SLA parameters applied in Cloud
environment