基于敏捷VNFs按需服务模型和深度强化学习方法的物联网任务调度新框架

IF 0.7 Q3 COMPUTER SCIENCE, THEORY & METHODS
Li Yang
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引用次数: 0

摘要

-物联网(IoT)的最新创新带来了需要快速响应时间和低延迟的物联网应用。雾计算已被证明是处理物联网应用的有效平台。由于物联网任务的异构性及其延迟敏感性,有效部署雾计算资源是一个重大挑战。为了利用物联网设备中的空闲资源,本文提出了一种边缘计算概念,将边缘任务卸载到附近的物联网设备。物联网辅助的边缘计算需要满足两个条件,一是边缘服务能够有效利用物联网设备的计算资源,二是卸载到物联网设备的边缘任务不干扰本地物联网任务。该方法主要包括两个阶段:边缘节点虚拟化和基于深度强化学习的任务调度。第一阶段提供了一个分层的边缘框架。在第二阶段,我们应用深度强化学习(DRL)来调度任务,同时考虑到任务的多样性和可用资源的异质性。仿真结果表明,本文提出的任务调度方法比现有方法具有更高的任务满意度和任务成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Task Scheduling Framework for Internet of Things based on Agile VNFs On-demand Service Model and Deep Reinforcement Learning Method
—Recent innovations in the Internet of Things (IoT) have given rise to IoT applications that require quick response times and low latency. Fog computing has proven to be an effective platform for handling IoT applications. It is a significant challenge to deploy fog computing resources effectively because of the heterogeneity of IoT tasks and their delay sensitivity. To take advantage of idle resources in IoT devices, this paper presents an edge computing concept that offloads edge tasks to nearby IoT devices. The IoT-assisted edge computing should meet two conditions, edge services should exploit the computing resources of IoT devices effectively and edge tasks offloaded to IoT devices do not interfere with local IoT tasks. Two main phases are included in the proposed method: virtualization of edge nodes, and task scheduling based on deep reinforcement learning. The first phase offers a layered edge framework. In the second phase, we applied deep reinforcement learning (DRL) to schedule tasks taking into account the diversity of tasks and the heterogeneity of available resources. According to simulation results, our proposed task scheduling method achieves higher levels of task satisfaction and success than existing methods.
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来源期刊
CiteScore
2.30
自引率
22.20%
发文量
519
期刊介绍: IJACSA is a scholarly computer science journal representing the best in research. Its mission is to provide an outlet for quality research to be publicised and published to a global audience. The journal aims to publish papers selected through rigorous double-blind peer review to ensure originality, timeliness, relevance, and readability. In sync with the Journal''s vision "to be a respected publication that publishes peer reviewed research articles, as well as review and survey papers contributed by International community of Authors", we have drawn reviewers and editors from Institutions and Universities across the globe. A double blind peer review process is conducted to ensure that we retain high standards. At IJACSA, we stand strong because we know that global challenges make way for new innovations, new ways and new talent. International Journal of Advanced Computer Science and Applications publishes carefully refereed research, review and survey papers which offer a significant contribution to the computer science literature, and which are of interest to a wide audience. Coverage extends to all main-stream branches of computer science and related applications
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