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A Comparative Study of Heterogenous Task-based Scheduling Techniques in a Cloud Environment

Cloud computing is increasingly recognized as a new way to provide IT resources (e.g., on-demand, computing, storage, network...) in a transparent way, and effective. Because of the heterogeneity environment of the cloud computing, the scalability can be supported, which is considered a fundamental feature for big data application to achieve performance, efficiency, load balance, and energy consumption. One of the main challenges of the cloud computing is resource management to satisfy the customers' requirements (e.g., Cost, QoS of resources.. .) and resource utilization of the data center. On the other hand, the Scheduling of resources among customers' tasks is considered the main issue of resource management. Therefore, resource scheduling algorithms is a vital research area to improve the total execution time (i.e., makespan), cost, efficiency, and load balance in the case of virtual resources. In this paper, we present a synthesis of the existing algorithms concerning scheduling customers' tasks based on heuristics approach in the cloud environment. Accordingly, the significant issues that play a role in the selection of the scheduling algorithm are provided.