A Task Scheduling Algorithm With Improved Makespan Based on Prediction of Tasks Computation Time algorithm for Cloud Computing

IEEE Access

Thar Baker¹  Abir Hussain¹  Panos Liatsis²  Belal Ali Al-Maytami³  Pingzhi Fan³ 

[1] Department of Computer Science, Liverpool John Moores University, Liverpool, U.K.;Department of Electrical Engineering and Computer Science, Khalifa University of Science and Technology, Abu Dhabi, United Arab Emirates;Institute of Mobile communication, Southwest Jiaotong University, Chengdu, China;

关键词: Scheduling algorithm;    task scheduling;    resource utilization;    cloud computing;   

DOI  :  10.1109/ACCESS.2019.2948704

来源: DOAJ

【 摘 要 】

Cloud computing is extensively used in a variety of applications and domains, however task and resource scheduling remains an area that requires improvement. Put simply, in a heterogeneous computing system, task scheduling algorithms, which allow the transfer of incoming tasks to machines, are needed to satisfy high performance data mapping requirements. The appropriate mapping between resources and tasks reduces makespan and maximises resource utilisation. In this contribution, we present a novel scheduling algorithm using Directed Acyclic Graph (DAG) based on the Prediction of Tasks Computation Time algorithm (PTCT) to estimate the preeminent scheduling algorithm for prominent cloud data. In addition, the proposed algorithm provides a significant improvement with respect to the makespan and reduces the computation and complexity via employing Principle Components Analysis (PCA) and reducing the Expected Time to Compute (ETC) matrix. Simulation results confirm the superior performance of the algorithm for heterogeneous systems in terms of efficiency, speedup and schedule length ratio, when compared to the state-of-the-art Min-Min, Max-Min, QoS-Guide and MiM-MaM scheduling algorithms.

【 授权许可】

Unknown