Yudong Huang, Tao Huang, Xinyuan Zhang, Shuo Wang, Hongyang Du, Dusit Niyato, Fei Richard Yu
{"title":"长距离工业物联网网络中基于 CSQF 的时敏流量调度","authors":"Yudong Huang, Tao Huang, Xinyuan Zhang, Shuo Wang, Hongyang Du, Dusit Niyato, Fei Richard Yu","doi":"arxiv-2409.09585","DOIUrl":null,"url":null,"abstract":"Booming time-critical services, such as automated manufacturing and remote\noperations, stipulate increasing demands for facilitating large-scale\nIndustrial Internet of Things (IoT). Recently, a cycle specified queuing and\nforwarding (CSQF) scheme has been advocated to enhance the Ethernet. However,\nCSQF only outlines a foundational equipment-level primitive, while how to\nattain network-wide flow scheduling is not yet determined. Prior endeavors\nprimarily focus on the range of a local area, rendering them unsuitable for\nlong-distance factory interconnection. This paper devises the cycle tags\nplanning (CTP) mechanism, the first integer programming model for the CSQF,\nwhich makes the CSQF practical for efficient global flow scheduling. In the CTP\nmodel, the per-hop cycle alignment problem is solved by decoupling the\nlong-distance link delay from cyclic queuing time. To avoid queue overflows, we\ndiscretize the underlying network resources into cycle-related queue resource\nblocks and detail the core constraints within multiple periods. Then, two\nheuristic algorithms named flow offset and cycle shift (FO-CS) and Tabu FO-CS\nare designed to calculate the flows' cycle tags and maximize the number of\nschedulable flows, respectively. Evaluation results show that FO-CS increases\nthe number of scheduled flows by 31.2%. The Tabu FO-CS algorithm can schedule\n94.45% of flows at the level of 2000 flows.","PeriodicalId":501280,"journal":{"name":"arXiv - CS - Networking and Internet Architecture","volume":"29 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"CSQF-based Time-Sensitive Flow Scheduling in Long-distance Industrial IoT Networks\",\"authors\":\"Yudong Huang, Tao Huang, Xinyuan Zhang, Shuo Wang, Hongyang Du, Dusit Niyato, Fei Richard Yu\",\"doi\":\"arxiv-2409.09585\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Booming time-critical services, such as automated manufacturing and remote\\noperations, stipulate increasing demands for facilitating large-scale\\nIndustrial Internet of Things (IoT). Recently, a cycle specified queuing and\\nforwarding (CSQF) scheme has been advocated to enhance the Ethernet. However,\\nCSQF only outlines a foundational equipment-level primitive, while how to\\nattain network-wide flow scheduling is not yet determined. Prior endeavors\\nprimarily focus on the range of a local area, rendering them unsuitable for\\nlong-distance factory interconnection. This paper devises the cycle tags\\nplanning (CTP) mechanism, the first integer programming model for the CSQF,\\nwhich makes the CSQF practical for efficient global flow scheduling. In the CTP\\nmodel, the per-hop cycle alignment problem is solved by decoupling the\\nlong-distance link delay from cyclic queuing time. To avoid queue overflows, we\\ndiscretize the underlying network resources into cycle-related queue resource\\nblocks and detail the core constraints within multiple periods. Then, two\\nheuristic algorithms named flow offset and cycle shift (FO-CS) and Tabu FO-CS\\nare designed to calculate the flows' cycle tags and maximize the number of\\nschedulable flows, respectively. Evaluation results show that FO-CS increases\\nthe number of scheduled flows by 31.2%. The Tabu FO-CS algorithm can schedule\\n94.45% of flows at the level of 2000 flows.\",\"PeriodicalId\":501280,\"journal\":{\"name\":\"arXiv - CS - Networking and Internet Architecture\",\"volume\":\"29 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - CS - Networking and Internet Architecture\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.09585\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Networking and Internet Architecture","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.09585","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.