Novel task assignment policies using enhanced hyper-heuristic approach in cloud

Abstract

Cloud computing plays a vital role in all fields of today's business. The processor sharing server farm is one of the most used server farms in the cloud environment. The key challenge for the mentioned server farms is to provide an optimal scheduling policy to process the computational jobs in the cloud. Many scheduling policies were introduced and deployed by the existing approaches to build an optimal cloud environment. The existing approaches of the heuristic algorithms such as meta-heuristic and hyper-heuristic approaches were the most frequently used scheduling algorithms for the past years. These approaches work well only in the limited types of tasks and resources in a processor sharing server farms in the cloud environment. In the proposed system, novel task assignment policies have been proposed by enhancing the hyper-heuristic approach for the type low task and high resource in the cloud environment. The results of the proposed approach are compared with the existing approaches and the performance evaluation of the proposed approach is also done. As a result, the proposed enhanced hyper-heuristic approach performs well for processor sharing server farms in the cloud environment.