Autonomous Workload Balancing in Cloud Federation Environments with Different Access Restrictions

Although federated cloud computing has emerged as a promising paradigm, autonomous orchestration of resource utilization within the federation is still required to be balanced on the basis of workload assignment at a given time. Such potential imbalance of workload allocation as well as resource utilization may lead to a negative cloudburst within the federation. The analytical models found in the literature do not provide explicit framework to provide dynamic measure of workload requirement within a cloud federation environment. An additional challenge is the adoption of operational restrictions from regulatory body, the federation, or the federation participants. The analytical models presented in this paper have addressed workload balancing within a federated cloud environment under the access control restrictions agreed between federation members. The proposed analytical models provide a closed form solution for access probability and resource utilization at a given time. The analytical results are evaluated at different degree of security within the cloud federation environment and efficiency of the proposed workload balancing models is demonstrated. The proposed models can be used for cloud services dimensioning to handle high computational demand.