An Equitable Profit Distribution Framework for SLA-Constrained and Dynamic Cloud Federations

The federated cloud paradigm boosts service delivery and profit generation through provider resource sharing. However, balancing long-term provider engagement, SLA compliance, and the dynamic interplay of job demands and capacity remains a key challenge in federated cloud economics. This paper proposes a framework for resource allocation in SLA-constrained federated clouds, addressing these challenges through optimization modeling and two heuristic algorithms. It introduces a dynamic fallback mechanism to handle capacity constraints, mitigate SLA violations, and prioritize delay-sensitive tasks, alongside variant methods leveraging job-specific characteristics for enhanced efficiency. Simulation results demonstrate that high-capacity federations achieve greater profits, reduced SLA violations, and improved scalability, while heterogeneous setups benefit from capacity diversity.