An enhanced architecture for big data task scheduling in cloud environment

Cloud computing is classified as one of the latest and fast growing technologies in the area of IT and engineering that offers resources such as software, hardware, network, storage, computing power as a service. The undeniable benefit of cloud computing is that it has elasticity that gives on-demand service. Therefore, users can access services anytime and anywhere without interruption, solving the problem of keeping huge hardware and storage in computers. However, how to deal with this increasing demand to allocate the jobs for processing is a hot issue. In addition, one of the main reason for users to send their data to the cloud is to reduce the cost while maintain their deadlines satisfied. Therefore, scheduling finds its main importance in allocating the jobs based on the resources. To this direction, in this paper we make a summary of some techniques used for scheduling and elaborate a novel architecture for processing and task scheduling adapted for big data applications. In this proposed architecture, each component has been defined in order to make smoother the implementation