Hybrid Algorithm for Profit Maximization in Hybrid Cloud

When customers own computing resources are not sufficient users utilize Infrastructure as a Service (IaaS) from public clouds. But the scheduling of task to the resources especially at the time of peak demand is a challenging issue. Also achieving better profit for the cloud provider is a problem. Previous proposed methods faced a challenge in the economical benefit and also hard to practice in real environment. The mathematical programming models done already experienced a slow response when the size of the problem scales up. The main objective is to improve the economic benefit of the IaaS provider with guaranteed Quality of Service (QoS). Hence to solve this problem, a hybrid algorithm incorporating Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO) is proposed for allocating user's task to the resources in hybrid cloud environment. The results show the improvement in the profit of cloud provider with fast response and better utilization of resources.