A Hybrid Grey Wolf Optimizer and Artificial Bee Colony Algorithm Used for Improvement in Resource Allocation System for Cloud Technology

Cloud computing is the next generation of technology which provide different service with the rule of pay and gain with the help of internet. These services consist of hardware and software used in different field of life. Due the growth of user in cloud environment the number of access and share system of technology increases which causes different issue and resource allocation system is one of them. In this paper for improvement in resource allocation system in VM a hybrid algorithm used because in some situation VM become underloaded and overloaded in cloud data centre due to lack of proper load balancing technique system. Therefore a hybrid technique used for improvement in VM allocation system. The hybrid technique consist of GWO and ABC algorithm three main section of GWO technique improve first improvment occur at local search section in this section ABC algorithm local search technique used second improvement occur at fitness function along with the energy parameter. The above proposed technique used to improve four main parameter of scheduling which are energy consumption, throughput network stability and average network executation time in resource allocation system in VM for cloud computing. The proposed technique result are compare with ABC algorithm , GWO algorithm, RAA algorithm based on those result the proposed algorithm improve 1.25 % accuracy and efficiency for resource allocation system in VM for cloud computing.