Resource Allocation in Cloud Computing Using SFLA and Cuckoo Search Hybridization

Abstract

The ‘cloud computing’ technology is requisite for modern technology. It has a notable facet called Resource Allocation. This given paper proposes Hybridized Optimization algorithm that is the combination of ‘Shuffled Frog Leaping Algorithm’ (SFLA) and ‘Cuckoo Search’ (CS) Algorithm. This technique overcomes the limitations of the existing works like HABCCS algorithm, GTS algorithm task, krill herd algorithm, also combines the advantages of SFLA and CS. In this method, SFLA section performs the preceding steps; initializing the request size, generating requests, and estimate fitness value of SFLA, sorting, dividing and evaluating the requests of user. The SFLA encompasses the advantage of higher speed convergence and easier implementation, with the capacity of having global optimization and are utilized widely in numerous areas. Then, CS algorithm executes operations like initializing, generating, evaluate fitness function, modification and then evaluating the new solutions. The CS algorithms possess the advantage of easier evaluation and it is utilized in complex situations. In this given system, the request speed, sizes are evaluated. Those evaluations are utilized in allocating the resources on the server-side. Less computed times are consumed in this technique. An experimental outcome displays that the approach performs well in contrasting with other related approaches.