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完整後設資料紀錄
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.advisor | 張時中(Shi-Chung Chang) | |
dc.contributor.author | Cheng-Yu Hsu | en |
dc.contributor.author | 徐晟育 | zh_TW |
dc.date.accessioned | 2021-06-17T00:10:49Z | - |
dc.date.available | 2021-02-22 | |
dc.date.copyright | 2021-02-22 | |
dc.date.issued | 2021 | |
dc.date.submitted | 2021-02-02 | |
dc.identifier.citation | References [3GPP TR 22.804] 3GPP, “TR 22.804 Study on Communication for Automation in Vertical Domains (Release 16)”, Version 16.1.0, Sep. 2018 [3GPP TR 23.734] 3GPP, “TR 23.734 Study on 5G Enhanced support of vertical and LAN services (Release 16),” Version 0.2.0, Sep. 2018 [3GPP TR 38.825] 3GPP, “TR 38.825 Study on NR industrial Internet of Things (IoT) (Release 16),” Nov. 2018 [5GPPP15] 5GPPP, '5G and the Factories of the Future,' Oct. 2015. [Online]. Available: https://libguides.nps.edu/citation/ieee [5GACIA19] 5G Alliance for Connected Industries and Automation, “5G for Connected Industries and Automation”, Feb. 2019. [Online]. Available: https://www.5g-acia.org/fileadmin/5G-ACIA/Publikationen/Whitepaper_5G_for_Connected_Industries_and_Automation/WP_5G_for_Connected_Industries_and_Automation_Download_19.03.19.pdf [APB19] A. Ademaj, D. Puffer, D. Bruckner et al, “Time Sensitive Networks for Flexible Manufacturing Testbed Characterization and Mapping of Converged Traffic Types,” Industrial Internet CONSORTIUM, Mar. 2019 [BuM18] S. F. Bush, G. Mantelet “Industrial Wireless Time-Sensitive Networking: RFC on the Path Forward,” Avnu Alliance White Paper, Jan. 2018. [Online]. Available: https://avnu.org/wp-content/uploads/2014/05/Industrial-Wireless-TSN-Roadmap-v1.0.3-1.pdf [BSH18] R. Barton, M. Seewald, J. Henry, “End-To-End Time-Sensitive Networking Connecting 5G Slices,” Technical Disclosure Commons, Nov. 2018 [CPR19] D. Cavalcanti, J. Perez-Ramirez, M. M. Rashid et al., “Extending Accurate Time Distribution and Timeliness Capabilities Over the Air to Enable Future Wireless Industrial Automation Systems,” Proceedings of the IEEE (Volume: 107, Issue:6), Mar. 2019 [CVV08] G. Cena, A. Valenzano, S. Vitturi, “Hybrid Wired/Wireless Networks for Real-Time Communications,” IEEE Industrial Electronics Magazine, Apr. 2008 [DBH11] D. Dimitrova, H. Berg, G. J. Heijenk et al., 'LTE Uplink Scheduling-Flow Level Analysis,' Proceeding of the 4th International Conference on Multiple Access Communications, Sep. 2011 [DPS16] E. Dahlman, S. Parkvall, J. Skold, “New 5G Radio-Access Technology,” in 4G LTE-Advanced Pro and The Road to 5G, 3nd ed. 2016, pp. 547-573. [ETSI TS 138 321] ETSI TS 138 321: “5G; NR; Medium Access Control (MAC) Protocol Specification (3GPP TS 38.321 version 15.3.0 Release 15),” Sep. 2018 [ETSI TS 123 501] ETSI TS 123 501: “3GPP; Technical Specification Group Services and System Aspects; System Architecture for the 5G System (5GS) (3GPP TS 23.501 version 16.5.0 Release 16),” 2020 [FiV19] B. Finley, A. Vesselkov, 'Cellular IoT Traffic Characterization and Evolution,' 2019 IEEE 5th World Forum on Internet of Things (Wo-IoT), Nov. 2019 [free5GC] free5GC Open Source, [Online]. Available: http://www.free5gc.org/roadmap [HLK19] M. Han, J. W. Lee, C. G. Kang et al., “5G K-SimSys: Open/Modular/Flexible System Level Simulator for 5G System,” IEEE International Symposium on Dynamic Spectrum Access Network (DySPAN), Jan. 2019 [HLP19] D. Hou, T. Liu, Yen-Ting Pan et al., “AI on Edge Device for Laser Chip Defect Detection,” IEEE 9th Annual Computing and Communication Workshop and Conference (CCWC), Jan. 2019 [IEEE 802.1Q] “IEEE Standard for Local and Metropolitan Area Networks–Bridges and Bridged Networks,” IEEE Std 802.1Q-2014 (Revision of IEEE Std 802.1Q-2011), pp. 1–1832, Dec. 2014 [IEEE 802.1Qbv] IEEE, “802.1Qbv—Enhancements for Scheduled Traffic,” [Online]. Available: http: //www:ieee802:org/1/pages/802:1bv:html, 2015 [IEEE TSN] IEEE, “Time-Sensitive Networking Task Group,” [Online]. Available: http://www.ieee802.org/1/pages/tsn.html, 2016 [IEEE16] “IEEE Standard for Information Technology–Telecommunications and Information Exchange between Systems Local and Metropolitan Area Networks–Specific Requirements - Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications,” in IEEE Std 802.11-2016 (Revision of IEEE Std 802.11- 2012), vol., no., pp.1-3534, Dec. 2016. [IEEE18] IEEE, “IEEE 802.1Q: IEEE Standard for Local and Metropolitan Area Networks – Bridges and Bridged Net- Works,” May 2018 [IMTS16] International Manufacturing Technology Show, 'Agenda for Industry 4.0 Machine Tools in Taiwan,' Sep. 2016, McCormick Place, Chicago [ITU17] ITU, “Technical and Operational Aspects of Internet of Things and Machine-to-Machine Applications by Systems in the Mobile Service (excluding IMT),” Annex 36 to Working Party 5A Chairman’s Report, Document 5A/TEMP/142(Rev.2), June 2017 [Iwa19] M. Iwamura, “5G Core Connectivity Options Migration Considerations,” NTT DOCOMO, May 2019 [JaN01] E. Jasperneite, P. Neumann, 'Switched Ethernet for Factory Communication,' ETFA 2001. 8th International Conference on Emerging Technologies and Factory Automation, Proceedings (Cat. No. 01TH8597). IEEE, 2001 [JLH18] J. Jiang, Y. Li, S. H. Hong, 'A Time-Sensitive Networking (TSN) Simulation Model Based on OMNET++,' IEEE International Conference on Mechatronics and Automation (ICMA), Aug. 2018 [Mes18] J. L. Messenger, “Time-Sensitive Networking: An Introduction,” IEEE Communications Standards Magazine, June 2018 [KJG19] M. Khoshnevisan, V. Joseph, P. Gupta et al., “5G Industrial Network with CoMP for URLLC and Time Sensitive Network Architecture,” IEEE Journal on Selected Areas in Communications, Apr. 2019 [Hsu20] K. S. Hsu, 'Research on MAC Scheduling of eLAA for QoS Aware and Affordable Wireless Access by Work Cell,' National Taiwan University Research Thesis, July 2020 [BDD13] K. Bauer, B. Diegner, J. Diemer et al., “Recommendations for Implementing the Strategic Initiative Industrie 4.0: Final Report of the Industries 4.0 Working Group,” Federal Ministry of Education and Research, Apr. 2013 [LTP19] J. A. López-Leyva, A. Talamantes-Álvarez, M. A. Ponce-Camacho et al., 'Industrial IoT Projects Based on Automation Pyramid: Constraints and Minimum Requirements,' The Internet of Things in the Industrial Sector pp 121-142, Aug. 2019 [MGR19] C. Mannweiler, B. Gajic, P. Rost et al., “Reliable and Deterministic Mobile Communications for Industrial 4.0: Key Challenges and Solutions for the Integration of the 3GPP 5G System with IEEE Time-Sensitive Networking,” Mobile Communication – Technologies and Applications;24. ITG-Symposium, IEEE, June 2019 [Mil19] A, Mildner, “Time Sensitive Networking for Wireless Networks – A State of the Art Analysis,” Network Architecture and Services, May, 2019 [NTA18] A. Nasrallah, A. S. Thyagaturu, Z. Alharbi et al., “Ultra-Low Latency (ULL) Networks: The IEEE TSN and IETF DetNet Standards and Related 5G ULL Research,” IEEE Communications Surveys and Tutorials, Sep. 2018 [NWG18] A. Neumann, L. Wisniewski, R. S. Ganesan et al., “Towards Integration of Industrial Ethernet with 5G Mobile Networks,” 2018 14th IEEE International Workshop on Factory Communication Systems (WFCS), July 2018 [OMN20] E. O’Connell, D. Moore, T. Newe, “Challenges Associated with Implementing 5G in Manufacturing,” 2020, [Online]. Available: https://www.mdpi.com/2673-4001/1/1/5/pdf [PAP18] D. Patel, M. I. Ashraf, A. Palaios, “5G Meets Time Sensitive Networking,” 2018, [Online]. Available: https://www.law.cornell.edu/cfr/text/47/part-96 [PBSI16] Panel Building System Integration, “Ethernet Adoption in Process Automation to Double by 2016,” 2013, [Online]. Available: http://www.pbsionthenet.net/article/58823/Ethernet-adoptionin-process-automation-to-double-by-2016.aspx [Sau05] T. Sauter, “Integration Aspects in Automation - A Technology Survey,” 10th IEEE Conference on Emerging Technologies and Factory Automation, 2005, pp. 255–263 [Sau10] T. Sauter, “The Three Generations of Field-Level Networks 2014—Evolution and Compatibility Issues,” Industrial Electronics, IEEE Transactions on, vol. 57, no. 11, pp. 3585–3595, Nov. 2010 [SGM92] C. Spanos, H. -F. Guo, A. Miller et al., 'Real-Time Statistical Process Control using Tool Data (Semiconductor Manufacturing),' IEEE Transactions on Semiconductor Manufacturing, Dec. 1992 [Sik03] B. Sikdar, “A Study of the Environment Impact of Wired and Wireless Local Area Network Access,” IEEE Transaction on Consumer Electronic, Apr. 2003 [SMB19] T. Striffler, N. Michailow, M. Bahr, “Time-Sensitive Networking in 5th Generation Cellular Networks – Current State and Open Topics,” 2019 IEEE 2nd 5G World Forum (5GWF), Nov 2019 [SSK11] T. Sauter, S. Soucek, W. Kastner, et al., 'The Evolution of Factory and Building Automation.' IEEE Industrial Electronics Magazine 5.3: 35-48, Oct. 2011 [STB14] S. B. H. Said, Q. H. Truong, M. Boc, “SDN-Based Configuration Solution for IEEE802.1 Time Sensitive Networking (TSN),” ACM SIGBED Review, Feb. 2019 [Tho05] J. -P. Thomesse, “Fieldbus Technology in Industrial Automation,” Proceedings of the IEEE, May 2005 [ToV99] E. Tovar, F. Vasques, 'Real-Time Fieldbus Communications using Profibus Networks,' IEEE Transactions on Industrial Electronics, Dec. 1999 [Tre16] H. Trsek, “Isochronous Wireless Network for Real-time Communication in Industrial Automation,” Springer-Verlag Berlin Heidelberg, 2016 [VaT14] A. Varghese, D. Tandur, “Wireless Requirements and Challenges in Industry 4.0,” IEEE International Conference on Contemporary Computing and Informatics (IC3I), 2014 [Wal16] T. Walter, “Time-Sensitive Networking and Industrial IoT,” July 2016, [Online]. Available: https://www.controleng.com/articles/time-sensitive-networking-and-industrial-iot/ [Wer20] J. Werb, 'What are the Cost Benefits of Industrial Wireless,' ISA100 Wireless Compliance Institute (WCI), 2020, [Online]. Available: https://blog.isa.org/cost-benefits-industrial-wireless-isa100-networks [WGS08] C. Wang, H. Ghenniwa, W. Shen, 'Real Time Distributed Shop Floor Scheduling Using an Agent-Based Service-Oriented Architecture,' International Journal of Production Research, May 2008 [WJR07] J. P. Womack, D. T. Jones, D. Roos, “The Machine that Changed the World: The Story of Lean Production--Toyota's Secret Weapon in the Global Car Wars that is Now Revolutionizing World Industry,” Simon and Schuster, 2007 [Zur14] R. Zurawski, “Industrial Communication Technology Handbook,” 2nd ed., CRC Press, Aug. 2014 | |
dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/65738 | - |
dc.description.abstract | 在自動化製造工廠中,工作單元是工廠自動化環境中資源的邏輯和策略安排,為工廠內各單機整合智慧化,提升製造的效率。工作單元與工廠管理層間使用工業乙太網路對單機、物料搬運及感測器間的控制指令和感測數據做優先級排程傳輸。時間敏感網路(TSN)是由IEEE802.1任務組開發的工業乙太網路,根據延遲、抖動和資訊流來類別八種保證延遲和相對品質流量,顯著改善時間同步和延遲,提高生產率。本文研究工作單元與工廠管理層間透過TSN橋接器傳輸,對於未來智慧製造多樣化且頻繁重組生產線的工廠,為了降低佈線成本和人力、降低擴廠的限制,需要考慮TSN橋接器無線化。以未來智慧製造工作單元和工廠管理層間通訊為例,大量數據即時傳輸是關鍵,而5G有效提升傳輸率、大頻寬和降低延遲,使用5G可降低佈署成本、提高佈設彈性和增加傳輸路徑靈活性等,因此未來工廠有望利用5G來實現更高的生產效率和靈活性。 針對自動化製造工廠中延遲要求嚴格的工作單元,上傳數據量大於下載,且日益增加,因此本研究選擇上傳至工作管理層的其中三種代表性流量: 工作指令、警告訊息及感測數據。”工作指令”是工作單元週期性上傳的程序要求,”警告訊息”則是因工作單元無預期超出正常運作範圍時隨機產生,而”感測數據”是感測器週期性取樣機台狀況數據。各應用於TSN的流量特性和延遲要求都不一樣,”工作指令” 上傳的延遲須小於10毫秒,”警告訊息”上傳的優先順序則須高於一般性”感測數據”。 本研究專注於工作單元控制器和工廠管理層間,藉由QoS映射和5G MAC層排程來支持TSN橋接器的無線化,主要研究問題和相應的挑戰為: P1) Translator設計問題: 依照IEEE 802.1Q 的分類,工作單元內的工令、警告訊息和感測數據分別屬於TSN Priority Code Point (PCP) 5、2、1。但TSN優先等級定義與5G QoS定義不同,如何依5G規範TS 23.501 於MAC層所定義的QoS Class Indicator (QCI ) 來映射支持,並且將TSN封包經由5G MAC層傳輸? C1) TSN PCP和5G QCI之間目前尚未有確定的優先等級轉換標準。兩者各自的類別數量不一樣外,對於QoS延遲定義也不同,PCP有相對優先級的概念,而QCI沒有。PCP延遲定義是從終端到終端,QCI是從User Equipment (UE)到User Plane Function (UPF),兩種定義全然不同,無法直接一對一映射。並且兩者的封包格式不同,因此如何映射並轉換封包格式是挑戰。 P2) 5G MAC排程問題: 在完成QoS映射之後,如何針對5G MAC層封包傳輸所需用到的邏輯通道資源間進行排程,來滿足工作單元各流量的延遲要求,且解決IEEE802.1Qbv GCL排程的不足? C2)目前尚未有針對TSN QoS的邏輯通道排程演算法,而所考慮的三種工作單元流量特性和QoS要求都不一樣,另外,我們所考慮的流量有包含確定性週期的工令和感測數據,還有隨機產生的警告訊息,而TSN排程缺乏支持彈性的流量和5G傳輸,因此針對所映射的QCI進行5G邏輯通道排程是新的挑戰。 P3) 模擬環境設計問題:如何設計5G支援TSN的MAC層架構,用來模擬工廠流量並實驗本研究提出的QoS映射和MAC排程,以評估是否能滿足從工作單元到工廠管理層的TSN QoS要求? C3) 如何模擬工作單元和工廠管理層間流量才能真實貼切工廠內實際狀況,以及在MAC層使用5G支援的TSN架構尚未有完善標準制定情形下,如何在既有概念規範上設計實驗QoS映射及MAC排程的模擬環境是一大挑戰。 針對以上問題與挑戰,本論文新提出並設計解決方案如下: M1) 針對工作單元所需保證延遲和相對品質提出映射原則。考慮TSN端到端延遲定義在所提出的架構中為對稱,且5G端到端QoS定義是TSN的一部份,本論文將PCP5(保證延遲<10ms)映射至保證延遲為一半的QCI 86(保證延遲<5ms),雖無法絕對保證PCP5的要求,但有高機率透過5G MAC排程達到。而將PCP2, 1映射到non-GBR類中延遲較寬鬆且有優先級別不同的QCI8,9達成相對優先。設計Translator經由封包格式處理將TSN封包視為5G的載荷來傳輸並依照我們提出的映射原則加上對應的MAC標頭。 M2)在5G MAC層新設計WGCL排程演算法,運用TSN IEEE 802.1Qbv門閥控制清單(GCL)原則為基礎,GCL為工廠管理員預先設定的門閥時間列表,缺乏彈性,而5G具備由UE向基地台傳送緩衝狀態回報(BSR)的功能。因此我們設計利用BSR中仍在UE排隊封包數當作動態分配各門閥開通時間的參數,讓門閥開通時間依據封包流量來調節,減少因門閥有不當空閒造成的延遲。基於PCP和QCI延遲要求導入加權輪詢(WRR)輔助計算,一方面使高優先級有較大的門閥時間比例來增加保證延遲的機率,另一方面區分相對優先級的門閥時間比例,進而滿足確定性週期和隨機產生的流量需求。 M3) 創新設計5G時間敏感網路MAC層之QoS排程實驗平台(5G-Enabled TSN Bridge, 5GenTSN-B)。主要採用C++和Python語言開發並整合NS3離散事件網路模擬器和5G-K開源模擬器。此平台包括下列模組: (一)封包產生及工作單元控制傳輸器,產生封包並由工作單元控制器依據TSN排程傳輸來模擬工作單元,(二)MAC層封包處理以及QoS映射的翻譯器,(3) QoS排程及優先等級處理器,實作WGCL排程演算法以及UE的優先級處理。另外平台內的工作單元模擬器管理者介面、動態顯示5G封包傳輸狀況和封包延遲監控介面,可供支持工作單元所需QoS排程演算法開發實驗用。 本論文的研究發現和貢獻如下: (1) 根據TSN PCP端到端和5G QCI UE到UPF間的延遲定義差異,設計5G和工作單元控制器所用TSN間的翻譯器,滿足保證延遲及相對QoS要求,因翻譯器造成的額外延遲為40μs~4μs。 (2) 提出WGCL排程演算法,參考 GCL分配門閥時間原則,結合BSR 和WRR使門閥時間隨流量改變外,也為各優先級加上權重做到保證延遲和相對QoS。解決TSN排程無法同時滿足確定性週期和隨機產生的流量需求。 (3) 設計並實作5GenTSN-B實驗平台,包括NS3模擬器用來模擬TSN封包、控制器排程和Translator QoS映射做封包格式處理,另外5G-K模擬器模擬基地台和移動裝置的排程和優先處理,用來評估本研究MAC層的QoS映射和WGCL排程,也可以做為未來TSN QoS在5G MAC的排程實驗平台。 (4) 5GenTSN-B實驗平台展示操作介面簡單且傳遞流程清楚的各GUI,並透過模擬展示影片順暢度和延遲曲線圖直覺觀察各優先級上傳封包的延遲。 | zh_TW |
dc.description.abstract | In an automated manufacturing factory, a work cell is a logical and strategic arrangement of resources in factory automation environment, which integrates a group of machines for intelligent operations and raising productivity. Communication between work cells and factory management often adopts industrial Ethernet to transmit with priority scheduling control commands and data among machines, material handling systems and sensors. Time Sensitive Network (TSN) is an industrial Ethernet network developed by the IEEE802.1 task group, which classifies eight classes of guaranteed delay and relative quality flow according to delay, jitter and information flow, significantly improves time synchronization, delay, and productivity. For smart factories with diversified manufacturing and frequent reorganization of production lines, in order to reduce wiring costs and labors, and the restrictions on factory expansion, it is necessary to consider wireless factory communication. Taking the needs for wireless communications between work cells and factory management in smart manufacturing as an example, real-time, high-rate and reliable data transmission is the key. Emergent 5G networks have the potential to effectively meet such demands. Adopting 5G can reduce factory deployment costs, raise configuration flexibility, and increase operation agility, etc. How to exploit 5G for wireless communication between work cells and factory management is therefore a significant research topic. For work cells with strict delay requirements in automated manufacturing factories, due to the amount of uploaded data is greater than that of downloads, this research selects three representative traffic that is uploaded to factory management: work instruction, warning message, and sensory data. 'Work instruction' is a periodic upload process request from the work cell, 'warning message' is randomly generated when the work cell unexpectedly exceeds the normal operating range, and 'sensory data' is the periodically sampling data of machine conditions. Each type of TSN traffic characteristics and delay requirements are different. The delay requirement of 'work instruction' is less than 10 milliseconds, and the priority of 'warning messages' must be higher than 'sensory data'. This research focuses on communication between a work cell and factory management. Supporting the wireless TSN bridge through QoS mapping and 5G MAC scheduling, the main research problems and corresponding challenges are: P1) Translator design problem: According to the classification of IEEE 802.1Q, the work instruction, warning message, and sensory data in the work cell belong to TSN Priority Code Point (PCP) 5, 2, and 1, respectively. However, TSN priority definitions are different from 5G QoS definitions. How to map and support the QoS Class Indicator (QCI) defined in the 5G MAC specification TS 23.501so that TSN packet can be transmit through 5G MAC? C1) There is currently no established QoS translation standard for TSN PCP and 5G QCI. In addition to the different number of categories, the definitions of QoS is also different. PCP has the concept of relative priority, while QCI does not. The E2E definition of PCP is from end station to end station, and QCI is from User Equipment (UE) to User Plane Function (UPF). The two definitions are completely different and cannot be directly mapped one to one. Also, the packet format of two are different. Therefore, how to map and translate the packet are big challenges. P2) 5G MAC scheduling problem: After QoS mapping, how to schedule the logical channel resources required for 5G MAC packet transmission to meet the delay requirements of each traffic from the work cell and solve the deficiency of TSN scheduling? C2) There is no logical channel scheduling algorithm for TSN QoS, and the three traffic characteristics and QoS requirements of the work cell we considered are different. In addition, the traffic we considered includes work instruction and sensory data with deterministic period, as well as randomly generated warning. TSN scheduling lacks support for flexible traffic and 5G transmission. Therefore, 5G logical channel scheduling for the mapped QCI is a new challenge. P3) Simulation environment design problem: How to design a 5G MAC layer architecture supporting TSN to simulate factory traffic and experiment with the QoS mapping and MAC scheduling we proposed in this research to evaluate whether it can meet the TSN QoS requirements from the work cell to factory management? C3) How to simulate the traffic between the work cell and the factory management to truly fit the actual situation in factories, and how to design an experimental simulation environment for QoS scheduling based on the existing conceptual specifications when the TSN architecture supported by 5G MAC has not been fully standardized yet is a big challenge. For the above problems and challenges, this study proposes and designs the following new solutions. M1) Propose mapping principle of the guaranteed delay and relative QoS for the work cell. Considering that the TSN E2E QoS definition is symmetric in the proposed architecture, and the 5G E2E delay definition is part of TSN, we map PCP5 (guaranteed delay<10ms) to QCI86 which is two times stricter (guaranteed delay<5ms). Although the requirement of PCP5 cannot be absolutely guaranteed, there is a high probability that the PCP5 requirement can be met through 5G MAC scheduling. Moreover, PCP2, 1 are mapped to non-GBR QCI8, 9 with looser delay and different priority levels to achieve relative priority. Translator is designed to transmit TSN packets as 5G payloads through packet format processing and add corresponding MAC header based on our QoS mapping principle. M2) A new WGCL scheduling algorithm is designed in the 5G MAC layer, using TSN IEEE 802.1Qbv Gate Control List (GCL) principle as the basis. GCL is a window time list preset by the factory administrator, which is inflexible. 5G has the ability to send the Buffer Status Report (BSR) from UE to gNB. Therefore, we design to use the number of packets queued in the UE by BSR as a parameter to dynamically allocate the window time of each gate, so that the window time is adjusted according to the traffic, reducing the delay caused by improper idleness of the window time. Based on the PCP and QCI delay requirements, the Weighted Round-Robin (WRR) auxiliary calculation is implemented. On the one hand, higher priority has a larger window time to increase the probability of guaranteed delay. On the other hand, it distinguishes the window time of relative priorities. And then meet the requirements of deterministic period and randomly generated traffics. M3) The innovative design of the experimental platform (5G-Enabled TSN Bridge, 5GenTSN-B) is for MAC QoS scheduling. Mainly adopt C++ and Python to develop and integrate NS3 discrete-event network simulator and 5G-K open-source simulator. This platform includes the following modules: (1) Packet generator and work cell controller, which generates and schedules packets by the work cell controller, (2) MAC layer packet processing and QoS mapping Translator, (3) QoS scheduling and priority processor, implement WGCL scheduling algorithm and UE priority handling. In addition, the work cell simulator interface, dynamically displays of 5G packet transmission status, and the packet delay monitoring interface, can be used for the development and experimentation of the QoS scheduling required by the work cell. The contributions of this research are as follows: (1) According to the different definitions of TSN PCP E2E and 5G QCI UE to UPF, the Translator between 5G and the TSN used by the work cell controller is designed to meet guaranteed delay and relative QoS requirements. The time for format processing is about μs level (40μs~4μs). (2) Propose the WGCL scheduling algorithm, refer to the GCL allocation window time principle, combine BSR and WRR to make the window time change with the amount of traffic, and also add weight to each priority to ensure guaranteed delay and relative QoS. Solve the problem that TSN scheduling cannot meet the requirements of deterministic period and randomly generated traffic at the same time. (3) Design and implement the 5GenTSN-B platform, including the NS3 simulator to simulate TSN packets, controller scheduling, and Translator QoS packet format processing. And the 5G-K simulator simulates the scheduler of base station and the priority handling of mobile station. This platform used to evaluate the QoS mapping and WGCL scheduling of MAC layer in this research, and can also be used as an experimental platform for future TSN QoS scheduling in 5G MAC. (4) The 5GenTSN-B experiment platform displays GUIs with simple operation interfaces and clear delivery processes, and intuitively observes the delay of each priority uploading packets through the smoothness of the video and delay curves. | en |
dc.description.provenance | Made available in DSpace on 2021-06-17T00:10:49Z (GMT). No. of bitstreams: 1 U0001-0202202115100000.pdf: 6407586 bytes, checksum: 814adbed1a042c06d2209a29f30689a2 (MD5) Previous issue date: 2021 | en |
dc.description.tableofcontents | Table of Contents 致謝 iii 中文摘要 iv Abstract viii List of Terms and Abbreviations xiii Table of Contents xvi List of Figures xix List of Tables xxiii Chapter 1 Introduction 1 1.1 Motivation: Wireless Network for More Flexible and Productive Factories 1 1.2 Literature Review 3 1.3 Scope of Thesis 7 1.4 Organization of Thesis 9 Chapter 2 Mac Layer QoS Scheduling of 5G-Enabled TSN Bridge for Work Cell: Problem Definitions 10 2.1 Demands of Wireless Network Communications for Work Cell in Smart Factories 11 2.1.1 Work Cell in Smart Factories 11 2.1.2 Three Levels of Factory Communications 12 2.1.3 Communication Demands between Work Cell and Factory Management 15 2.1.4 Current Cell Level Communication Network Solutions 18 2.1.5 Advantages of Wireless Communication in Work Cell-Factory Communication 20 2.2 Time Sensitive Network (TSN) for Work Cell Level Communication 22 2.2.1 TSN Overview and Architecture 22 2.2.2 TSN for Work Cell Level 25 2.2.3 TSN QoS and Priority Scheduling 27 2.3 Introduction to 5G 31 2.3.1 5G Overview and Architecture 31 2.3.2 5G QoS and Priorities 37 2.4 Problem Definitions and Challenges of MAC QoS Scheduling for 5G-Enabled TSN Bridge 41 2.4.1 5G as a Wireless Support of Work Cell TSN 41 2.4.2 Design of 5G-Enabled TSN Bridge MAC Layer Architecture 44 2.4.3 QoS Mapping and Scheduling in 5G-Enabled TSN Bridge: Design Problem Definitions 48 2.4.4 Design Challenges 50 Chapter 3 QoS Mapping and Translator Design for Work Cell Level 53 3.1 Assumptions and QoS Mapping Principles 53 3.1.1 Scenario Assumptions and Design of QoS Mapping Principles 53 3.2 Packet Formation and Procedures of QoS Mapping by Translator 58 3.2.1 Packet Format Processing 58 3.2.2 Translator Sequence Diagram 60 3.3 Summary 62 Chapter 4 5G MAC Scheduling for Cell-to-Factory TSN Bridge 63 4.1 Deterministic Queuing Analysis of IEEE802.1Qbv GCL Scheduling 63 4.1.1 Modeling of Gate Control List (GCL) Scheduler 64 4.1.2 Deficiency for Application to 5G Enabler in Delay Performance 68 4.2 Wireless GCL (WGCL) Algorithm Design for QoS Scheduling 71 4.2.1 Logical Channel Scheduling and Buffer Status Report 71 4.2.2 Innovative WGCL Algorithm Design 75 4.3 Performance Evaluation of WGCL Scheduling 80 4.3.1 Numerical Window Time Allocation Analysis 81 4.3.2 Simulation Evaluation of WGCL 84 4.4 Summary 100 Chapter 5 5GenTSN-B Platform 101 5.1 Platform Overview and Implementation 101 5.2 User Interface and Display Window Design 105 5.2.1 Work Cell UI 106 5.2.2 5G-Enabled TSN Bridge Display Window 108 5.2.3 Factory Management Monitor UI 108 5.3 5GenTSN-B Platform Procedures 111 5.4 Demo Scenario: Diverse Periodic Traffic and Congestion 113 Chapter 6 Conclusions and Future Work 118 6.1 Conclusions 118 6.2 Future Work 119 References 121 | |
dc.language.iso | en | |
dc.title | 工作單元所用5G時間敏感網路之MAC層服務品質排程設計 | zh_TW |
dc.title | QoS Scheduling Design in MAC Layer of 5G-Enabled TSN for Work Cell | en |
dc.type | Thesis | |
dc.date.schoolyear | 109-1 | |
dc.description.degree | 碩士 | |
dc.contributor.oralexamcommittee | 蔡志宏(Zse-Hong Tsai),絲國一(Kou-I Szu),侯廷昭(Ting-Chao Hou),魏宏宇(Hung-Yu Wei),蘇炫榮(Hsuan-Jung Su) | |
dc.subject.keyword | QoS排程,5GenTSN-B實驗平台,時間敏感網路 (TSN),5G-K模擬器,智慧工廠,工作單元,邏輯通道排程,媒體接取層 (MAC),NS3,門閥控制清單 (GCL), | zh_TW |
dc.subject.keyword | QoS scheduling,5GenTSN-B platform,Time Sensitive Network (TSN),5G-K Simulator,smart factory,work cell,logical channel scheduling,Media Access Control (MAC),NS3,Gate Control List (GCL), | en |
dc.relation.page | 125 | |
dc.identifier.doi | 10.6342/NTU202100385 | |
dc.rights.note | 有償授權 | |
dc.date.accepted | 2021-02-03 | |
dc.contributor.author-college | 電機資訊學院 | zh_TW |
dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
顯示於系所單位: | 電機工程學系 |
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