Delay-Aware Associate Tasks Scheduling in the Cloud Computing

Abstract

Cloud computing can provide the dynamic and elastic virtual resources for the users to execute the large-scale computing tasks. It has become the hot spot in the academic and industry fields. The tasks scheduling plays an important role in the Cloud computing. It should adopt the scheme to dispatch the computing tasks to the appropriate resources considering some QoS constraints, e.g., task execution time, task completion time, resource utilization, and cost. At present, the scheduling schemes should consider the associate tasks scheduling problem with some constraints in the real applications. In this paper, concerning the delay of the associated tasks scheduling in cloud computing, a structured-based hierarchical task models was discussed and the associated task scheduling algorithms based on delay-bound constraint (SAH-DB) was proposed. The scheduling scheme based on the tasks model can improve the task execution concurrency. The tasks in the parallel structure can be grouped into one task set belonging to the same task layer. Through the calculation of the total tasks execution time-bound in each task layer, the associated task was dispatched to the resources with the minimum execution time. Extensive experimental results demonstrated that the proposed SAH-DB algorithms can achieve better performance than CPM and TS-Sim algorithm in the terms of the total execution cost and resource utilization.