Multi-objective Optimization of Data Placement in a Storage-as-a-Service Federated Cloud

Cloud federation enables service providers to collaborate provide better services customers. For cloud storage services, optimizing customer object placement for a member of is real challenge. Storage, migration, and latency costs need be considered. These are contradictory in some cases. In this article, we modeled as multi-objective optimization problem. The proposed model takes into account parameters related the local infrastructure, federated environment, workloads, their SLAs. resolving problem, propose CDP-NSGAII IR , Constraint Data Placement matheuristic based on NSGAII with Injection Repair functions. injection function aims enhance solutions’ quality. It consists calculate solutions using an exact method then inject them initial population NSGAII. repair ensures that obey problem constraints so prevents from exploring large sets unfeasible solutions. reduces drastically execution time Experimental results show improves HV by up 94% 60%, respectively, while average 68%.