Optimized Contract-Based Model for Resource Allocation in Federated Geo-Distributed Clouds

In the era of Big Data, with data growing massively in scale and velocity, cloud computing its pay-as-you-go model continues to provide significant cost benefits a seamless service delivery for consumers. The evolution small-scale large-scale geo-distributed datacenters operated managed by individual Cloud Service Providers (CSPs) raises new challenges terms effective global resource sharing management autonomously-controlled datacenter resources towards globally efficient allocation model. Earlier solutions clouds have focused primarily on achieving efficiency sharing, that although tries maximize allocation, results inefficiencies local provi ders leading unfairness their revenue profit earned. this paper, we propose contracts-based federated allows CSPs establish contracts apriori defined time intervals during 24 hour period. Based established contracts, employ duration aware job scheduling provisioning algorithm enables jobs complete meet response requirements while both fairness proposed techniques are evaluated through extensive experiments using realistic workloads generated SHARCNET cluster trace. demonstrate effectiveness, scalability