长距离工业物联网网络中基于 CSQF 的时敏流量调度

Yudong Huang, Tao Huang, Xinyuan Zhang, Shuo Wang, Hongyang Du, Dusit Niyato, Fei Richard Yu
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引用次数: 0

摘要

蓬勃发展的时间关键型服务,如自动化制造和远程操作,对促进大规模工业物联网(IoT)提出了越来越高的要求。最近,有人提倡采用循环指定队列和转发(CSQF)方案来增强以太网。然而,CSQF 只概述了一种基础设备级基元,而如何实现全网流量调度尚未确定。之前的尝试主要集中在局部区域范围内,因此不适合长距离工厂互连。本文设计了循环标签规划(CTP)机制,这是 CSQF 的第一个整数编程模型,它使 CSQF 在高效的全局流量调度中变得切实可行。在 CTP 模型中,通过将长距离链路延迟与循环排队时间解耦,解决了每跳循环对齐问题。为避免队列溢出,我们将底层网络资源离散化为与周期相关的队列资源块,并详细说明了多个周期内的核心约束条件。然后,我们设计了名为 "流量偏移和周期移动(FO-CS)"和 "Tabu FO-CS "的两种启发式算法,分别用于计算流量的周期标记和最大化可调度流量的数量。评估结果表明,FO-CS 使可安排流量的数量增加了 31.2%。Tabu FO-CS 算法可以在 2000 个流量的水平上调度 94.45% 的流量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CSQF-based Time-Sensitive Flow Scheduling in Long-distance Industrial IoT Networks
Booming time-critical services, such as automated manufacturing and remote operations, stipulate increasing demands for facilitating large-scale Industrial Internet of Things (IoT). Recently, a cycle specified queuing and forwarding (CSQF) scheme has been advocated to enhance the Ethernet. However, CSQF only outlines a foundational equipment-level primitive, while how to attain network-wide flow scheduling is not yet determined. Prior endeavors primarily focus on the range of a local area, rendering them unsuitable for long-distance factory interconnection. This paper devises the cycle tags planning (CTP) mechanism, the first integer programming model for the CSQF, which makes the CSQF practical for efficient global flow scheduling. In the CTP model, the per-hop cycle alignment problem is solved by decoupling the long-distance link delay from cyclic queuing time. To avoid queue overflows, we discretize the underlying network resources into cycle-related queue resource blocks and detail the core constraints within multiple periods. Then, two heuristic algorithms named flow offset and cycle shift (FO-CS) and Tabu FO-CS are designed to calculate the flows' cycle tags and maximize the number of schedulable flows, respectively. Evaluation results show that FO-CS increases the number of scheduled flows by 31.2%. The Tabu FO-CS algorithm can schedule 94.45% of flows at the level of 2000 flows.
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