QoE-Oriented Dependent Task Scheduling Under Multi-Dimensional QoS Constraints Over Distributed Networks

IF 4.7 2区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Xuwei Fan;Zhipeng Cheng;Ning Chen;Lianfen Huang;Xianbin Wang
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Abstract

Task scheduling as an effective strategy can improve application performance on computing resource-limited devices over distributed networks. However, existing evaluation mechanisms for application completion fail to depict the complexity of diverse applications and time-varying networks, which involve dependencies among tasks, computing resource requirements, multi-dimensional quality of service (QoS) constraints, and limited contact duration among devices. Furthermore, traditional QoS-oriented task scheduling strategies struggle to meet the performance requirements without considering differences in satisfaction and acceptance of the application, leading to application failures and resource wastage. To tackle these issues, a quality of experience (QoE) cost model is designed to evaluate application completion, depicting the relationship among application satisfaction, communications, and computing resources over the time-varying distributed networks. Specifically, considering the sensitivity and preference of QoS, we model the different dimensional QoS degradation cost functions for dependent tasks, which are then integrated into the QoE cost model. Based on the QoE model, the dependent task scheduling problem is formulated as the minimization of overall QoE cost, aiming to improve the application performance over the time-varying distributed networks, which is proven Np-hard. Moreover, a heuristic Hierarchical Multi-queue Task Scheduling (HMTS) algorithm is proposed to address the QoE-oriented task scheduling problem among multiple dependent tasks, which utilizes hierarchical multiple queues to determine the optimal task execution order and location according to different dimensional QoS priorities. Finally, extensive experiments demonstrate that the proposed algorithm can significantly improve the satisfaction of applications.
分布式网络多维QoS约束下面向QoS的依赖任务调度
任务调度作为一种有效的策略,可以提高分布式网络中计算资源有限的设备上应用程序的性能。然而,现有的应用完成评估机制未能描述不同应用和时变网络的复杂性,这些复杂性涉及任务之间的依赖关系、计算资源需求、多维服务质量(QoS)约束以及设备之间有限的接触时间。此外,传统的面向qos的任务调度策略在不考虑应用程序满意度和接受度差异的情况下难以满足性能需求,从而导致应用程序失败和资源浪费。为了解决这些问题,设计了一个体验质量(QoE)成本模型来评估应用程序的完成情况,描述了时变分布式网络中应用程序满意度、通信和计算资源之间的关系。具体地说,考虑到QoS的敏感性和偏好性,我们为依赖任务建立了不同维度的QoS退化代价函数,然后将其集成到QoS代价模型中。在QoE模型的基础上,将相关任务调度问题归结为总体QoE成本的最小化,以提高时变分布式网络的应用性能,并证明了该方法的Np-hard性。此外,提出了一种启发式分层多队列任务调度算法(HMTS),该算法利用分层多队列根据不同维度的QoS优先级确定任务的最优执行顺序和位置,解决了面向QoS的多依赖任务之间的任务调度问题。最后,大量的实验表明,该算法可以显著提高应用的满意度。
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来源期刊
IEEE Transactions on Network and Service Management
IEEE Transactions on Network and Service Management Computer Science-Computer Networks and Communications
CiteScore
9.30
自引率
15.10%
发文量
325
期刊介绍: IEEE Transactions on Network and Service Management will publish (online only) peerreviewed archival quality papers that advance the state-of-the-art and practical applications of network and service management. Theoretical research contributions (presenting new concepts and techniques) and applied contributions (reporting on experiences and experiments with actual systems) will be encouraged. These transactions will focus on the key technical issues related to: Management Models, Architectures and Frameworks; Service Provisioning, Reliability and Quality Assurance; Management Functions; Enabling Technologies; Information and Communication Models; Policies; Applications and Case Studies; Emerging Technologies and Standards.
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