Cloud computing is a most recent methodology that is developing quicker step by step because of its compelling component and security. Distributed computing gives an approach to get to the information from wherever whenever. This component makes it famous in light of the fact that it decreases the weight of the clients. Distributed computing gives the administrations like framework, stage and programming as an administration on it. Because of these elements the Size of information on cloud in expanded and it impacts on the productivity of cloud. To defeat the issue like this planning of assignment on information is the best alternative. Work process planning for logical registering frameworks is one of the most testing issues that spotlights on fulfilling client characterized nature of administration necessities while limiting the work process execution cost. So, to lessen the cost, cloud condition, has been conveyed in cloud condition, assets will increment yet its usage is another test. To keep up and use assets in the distributed computing planning component is required. Numerous calculations and conventions are utilized to deal with the parallel employments and assets which are utilized to improve the exhibition of the CPU in the cloud condition. This work Particles swarm Optimization (PSO) and Gray Wolf Optimization (WCA) are utilized for successful booking. This work depends on the advancement of Total execution time and absolute execution cost. The consequences of the proposed methodology are observed to be successful in contrast with existing strategies. Insight advancement Particle Swarm enhancement is utilized which is instated by Pareto circulation. WCA is utilized to merge the choice of Virtual Machine (VM) relocation by its union to limit cost and time as outlined by Total execution time (TET) and Total execution cost (TEC). It is inferred that WCA performs better in contrast with existing FUZZY_HEFT calculation.