Assorted Cat Swarm Optimisation for Efficient Resource Allocation in Cloud Computing

Cloud computing paradigm is one of the most extensively researched topic. It enables providing hardware and software resources according to pay-per-use mechanism with minimalistic requirements for on premise infrastructure. However, the exponentially rising resource requests need to be gratified by an efficient allocation algorithm. Various such algorithms have been proposed including Cat Swarm Optimization (CSO) which is inspired by the foraging nature of cats. This paper presents a modification in CSO with the addition of a crossover technique (Uniform Crossover) to improve its Total Execution Cost. This new algorithm has been termed as Assorted Cat Swarm Optimization (ACSO) Algorithm. On comparing the results obtained through simulations, it is observed that ACSO performed better than CSO in terms of Total Execution Cost.