Hybrid SFLA-GA algorithm for an optimal resource allocation in cloud

The cloud computing is a type of computing model which in the recent years has acquired attention due to its varied application and ease of use. It is a convenient and quick way of accessing shared resources at any time and at any place by means of using internet which is realized effectively for sharing of software and hardware resources. For managing the cloud resource and dynamic configuration for all types of underlying hardware resources that are comprised in virtualization technology to provide services to users with virtual machines (VM) as the basic unit, a key role is played by virtualization technology. Optimizing the objective in satisfying the constraint, the purpose of deploying VM is to realize the ideal outcome by altering the layout as well as the placement of all the VM. The allocation of the cloud resources to that of the user based on the request is a problem that is NP Hard. Heuristic methods are utilized for optimizing the resource allocation. The shuffled frog leaping algorithm (SFLA) has the benefit of easier implementation and high speed convergence with the capability of having global optimization and are used widely in various areas. The Genetic Algorithms (GAs) are the iterative stochastic optimization based methods that are based on the natural selection principles and their evolution. For this work, there is a hybrid SFLA-GA used for obtaining the allocation of optimal resources in the cloud computing.