ABSTRACT
Cloud computing plays an important role in sharing of resources concurrently with all big data applications. Handling multiple resources and regulating the path for information transfer to all the big data applications is a tedious task. In cloud computing, user request scheduling is take place by allotting the task to the best data center for execution. Locating the appropriate data center by determining efficiency value is one of the primary difficulties in cloud computing. Despite the fact there are many different types of scheduling algorithms still have certain limitations and a few such limitations have been quantified in existing approaches. In the proposed work an Optimal and Dynamic Allocation Policy (ODAP) has been introduced for allocating the task to the efficient data center (EDC). The effectiveness of the proposed approach was assessed utilising assessment metrics.
