This paper examines possibilities for improving the existing strategies of consistency management for highly-distributed transactional database in a hybrid cloud environment. With a detailed analysis of the existing consistency models for distributed database and standard strategies including Classic, Quorum and Tree Based Consistency (TBC), it is concluded that an improved advanced model of so-called visible adaptive consistency needs to be applied in a highly-distributed cloud environment, as necessary and sufficient degree of synchronization of all replicas. Along with the proposed model, research and development of an advanced novel strategy for consistency management Rose TBC (R-TBC) approach has been conducted, by improving standard TBC approach. Regarding implementation, a specific agglomerative Rose Tree Algorithm (RTA) has been developed, based on Bayesian hierarchical clustering and Graph Partitioning Algorithm - Multidimensional Data Clustering (GPA-MDC) intelligent partitioning of transactional Cloud Database Management System (CDBMS). The final result is constructed R-TBC model that changes in accordance with dynamic changes of entire heterogeneous CDBMS environment.

— The aim of this paper is to present differences between ITIL model from 2007 and ITIL model from 2011. IP Multimedia Subsystem is chosen as the test architecture for the implementation of these two models. The paper contains two different measurements. In the first measurement are taken only 2 parameters: time period needed for the implementation and the number of employees needed for the implementation. Results have showed that the model from 2011 is better for 12% than the model from 2007. In the second measurement are taken all Key Performance Indicators for 15 ITIL processes: Financial Management, Service Portfolio Management, Service Level Management, Capacity Management, Availability Management, IT Service Continuity Management, Information Security Management, Supplier Management, Change Management, Service Asset and Configuration Management, Release and Deployment Management, Service Validation and Testing, Incident Management, Problem Management and Continual Service Improvement process. Results in this measurement have showed that the model from 2011 is better for 10% than the model from 2007.