臺灣博碩士論文加值系統

在數位自動化工廠中，工作單元是工廠自動化環境中的一種模組化生產資源佈置，用以達到彈性生產的質量，並降低成本。工廠管理層與工作單元間聯網通訊則透過工業乙太網路交換機，例如有線時間敏感網路(TSN)交換機，來傳輸即時的工廠控管制指令、工作單元機台配置、各樣感測數據等等。對於少量多樣及頻繁重組生產線的工廠，為了降低換線成本、擺脫環境對佈線的限制、提升工作單元間重組的彈性，有需要考慮無線化。
針對中小型智慧工廠無線化問題，我們主要的研究問題以及相應的挑戰為:
P1. 無線化重點:中小型智慧工廠通訊無線化的重點為何?
C1. 工廠通訊包含工廠，單元和機器等三個級別，各層級的通訊服務需求載量及品質不同，而異質通訊網路及邊緣運算所提供的服務種類、品質與成本也各不相同。智慧工廠無線化的需求、效益因工廠型態各不相同，該在哪一層級無線化，既要考慮需求與技術服務匹配也要考慮成本與效益。
P2. 可負擔性:中小型工廠工作單元使用TSN交換機來連網工廠層控管與運算服務，既滿足資訊傳輸品質(QoS)差異要求，又可負擔的無線化選項為何?
C2. 目前TSN QoS (在IEEE 802.1Q稱為PCP)包含保證和相對QoS等級共八種，工作單元具代表性資訊傳輸需求包括:工作單元對外的工令(PCP 4,保證延遲)、機台警訊(PCP 2, excellent effort)、感測數據(PCP 1, best effort)。Wi-Fi可以支援相對QoS, 但無法保證QoS，而5G 服務雖預期可更符合需求，但對於中小型工廠是較無法負擔的。
P3. QoS 映射問題: 針對中小型製程自動化工廠，例如使用中低階CNC工具機的工作單元，工令的通訊傳輸要求約為60毫秒的延遲、警告傳輸延遲小於感測數據，分別對應TSN PCPs4、2、1其延遲定義與eLAA的不同，如何以無線網路eLAA MAC layer的QCI(TS 23.203)來映射支持?
C3. 目前尚未有TSN和eLAA QoS之間的轉換標準。除了兩者各自的類別數量不同外，其對於QoS延遲定義也不同，TSN是端到端，eLAA是UE到GW。選擇太鬆的eLAA class無法符合對應TSN QoS, 選擇太嚴的class對應又會導致過度配置使用無線資源。
P4. eLAA MAC Scheduling問題: 在完成QoS映射之後，如何針對eLAA MAC的有限執照與非執照頻譜資源進行邏輯通道排程(或稱UE內排程)滿足所對應的各QCI?
C4. 目前尚未有針對TSN QoS aware的邏輯通道排程演算法，而所考慮的TSN QoS流量除了QoS要求不同，工作單元和工廠管理層所產生的流量也各有不同的特性。
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. 研析各層級的通訊服務量及品質需求並調查市場實際案例趨勢，指出宜優先考慮單元級別、單元控制器與工廠控管間的無線化。
M2. 相較於5G，選擇eLAA是對中小型工廠較經濟的方案，而相較於Wi-Fi和LTE，eLAA整體效能較優，因此提出eLAA促成之工作單元與工廠控管間無線接取架構。其中，特別專注研究影響傳輸品質的MAC排程，以使eLAA利用執照頻譜可保證工令(TSN PCP 4)的低延遲傳輸，使機台warning延遲(PCP 2)相對低於感測數據傳輸(PCP 1)，並利用免執照頻譜支持工作單元TSN PCP 1之大數據傳輸，同時提升整體QoS。
M3. 針對所需相對優先、保證QoS提出映射原則。考慮TSN QoS延遲定義在所提出框架的結構對稱性，並且在QoS 延遲定義方面, eLAA是TSN的一部分, 本研究將 PCP 4映射至延遲小於其一半的QCI-84對應，雖無法絕對保證，但有很高機率透過eLAA的排程達成PCP 4的要求．並將PCP 2和1 映射至較寬鬆但有延遲區隔的QCI-7和6達成相對優先.
M4. 論文研究運用TSN的時間感知整形排程演算法中周期時間窗口傳輸原則，設計創新的時間感知整形-相對優先級(TAS-RP) 排程演算法來排程保證延遲的周期傳輸，並加入非搶占優先機制來達成相對優先，來進行排程映射後的各QCI。
上述創新設計經實作為以eLAA來促成工作單元-工廠間MAC層聯網之QoS排程實驗平台(Scheduling eLAA for Wireless TSN, ScheLAA-WTSN)。主要採用Python語言開發並整合軟體定義無線電。此平台包括工作單元控制器仿真器、支持eLAA的TSN交換機和網絡仿真器以及工廠管理仿真器，可供支持工作單元所需QoS aware排程演算法開發實驗用。
本論文研究的發現與貢獻包含:(1) 研析中小型過程自動化工廠單元級別通訊需求約60毫秒，指出單元級別無線通訊是未來中小型工廠數位轉型的重點之一。(2) 鑑於中小型工廠控管與工作單元間無線寬頻網路傳輸需要保證工令傳輸低延遲及警訊傳輸延遲須低於感測數據傳輸，選定以服務成熟的LTE、載波聚合及先聽後送等技術為基礎的eLAA網路，同時使用執照與非執照頻譜，以經濟有效的eLAA 運用MAC層邏輯通道排程，來支持中小型工廠所需TSN QoS。(3) 根據所考慮工作單元選擇具代表性的TSN QoS保證及相對延遲要求，分別映射至保證延遲類別和兩個相對品質的類別，使得eLAA能合適的處理對應的TSN QoS。(4) 提出TAS-RP排程演算法，考慮PCP 4週期性arrival，配置PCP 4的週期傳輸時段，並且在非PCP 4傳輸時段，透過非搶占優先使PCP 2傳輸優先於PCP 1。(5) 透過模擬實驗發現在飽和流量情境下，TAS-RP能夠保證PCP 4每個封包的延遲，並維持PCP 2平均延遲低於PCP 1，且相較於標準，PCP 4平均延遲降低約2~54%及PCP 2封包延遲低於PCP 1封包延遲比率最高可改善約68%，達成QoS aware、保證中小型工廠work cell 工令上傳延遲、警告和感測數據間上傳的相對延遲要求。

In an digitally automated factory, a work cell is designed to be modular to achieve flexibility and reduce costs. The factory management (FM) and work cell communicate through industrial Ethernet switches, such as wired time sensitive network (TSN) switches, to transmit real-time control commands, machine configuration, various sensory data, etc. For factories with a small number of diverse production lines that are frequently reorganized, it is necessary to consider wireless communication for reducing the cost of changing wires, overcoming restrictions on wiring, and improving flexibility for the reorganization of work cells.
In view of the wireless problem of smart factories that are small- and medium-sized enterprises (SMEs), the main research problems and associated challenges are:
P1. Wireless Focus: What is the focus of wireless communication in smart SME factories?
C1. Factory communication occurs at the factory, cell, and machine levels, and the capacity and quality of communication services required at each level are different. Furthermore, the type, quality, and cost of services provided by heterogeneous communication networks and edge computing differ. For the determination of the level that is the focus of wireless communication, it is necessary to consider not only the matching of requirements and technical communication services, but also the cost and benefits of the services.
P2. Affordability: If an SME factory’s work cell communicate with the FM and request for computing services through TSN switches, what are the affordable wireless options that can provide the required Quality of Service (QoS)?
C2. Currently, eight TSN QoS classes (called priority code point (PCP) in IEEE 802.1Q) include both guaranteed and relative QoS. Representative communication requirements of work cells include work instructions, warnings, and sensory data. Wi-Fi can support relative QoS but not guaranteed QoS. Although 5G technology is expected to be better suited for meeting all requirements, it is unaffordable for SME factories.
P3. QoS mapping: In terms of latency, Process-automated SME factories, such as factories that use work cells comprising low- and medium-level Computer Numerical Control machine tools, require a work instruction for about 60 ms and warning latency lower than sensory data latency, corresponding to TSN PCP 4, 2, and 1. The delay definition of the TSN is different from that of enhanced Licensed Assisted Access (eLAA). How should the QoS class indicator (QCI; TS 23.203) of the eLAA Media Access Control (eLAA MAC) layer be used to map the TSN PCP?
C3. There is currently no standard for QoS mapping between the TSN and eLAA. TSN and eLAA have different numbers of QoS classes and different delay definitions. Furthermore, TSN is end-to-end, while eLAA is user equipment (UE)-to-gateway. If the QCI is chosen to be too loose, the corresponding TSN QoS cannot be met, and a very strict QCI will lead to resources being overused.
P4. MAC scheduling: After QoS mapping, how should the logical channel transmission in the limited licensed and unlicensed bands in eLAA MAC be scheduled (also termed intra-UE scheduling) to satisfy the corresponding QCIs?
C4. There is no TSN QoS-aware logical channel (LC) scheduling algorithm. In addition to different QoS requirements for traffic between the work cell and the FM, their characteristics are also different.
For the above problems and challenges, this study proposes and designs the following new solutions.
M1. Analyze the communication service volume and quality requirements at each level and investigate actual market trends. The cell level is identified as the focus of wireless communication.
M2. For SME factories, eLAA is not only more economical than 5G but also shows better overall performance than Wi-Fi and long-term evolution (LTE). Therefore, an eLAA-enabled TSN framework is proposed for wireless access between the work cell and the FM. The focus of this study was on MAC scheduling for ensuring low-latency transmission of work instructions in the licensed band when the warning latency is better than the sensory data latency, and in the supplementary unlicensed band to support the large amount of sensory data transmission when seeking to improve the overall QoS.
M3. A mapping principle is proposed for the required relative priority and guaranteed QoS. Considering the structural symmetry of the TSN latency definition in the proposed framework and in terms of the QoS delay definition (eLAA is part of TSN), this study mapped PCP 4 to QCI-84, whose delay is less than half of the maximum delay permissible for the work instruction transmission. Although it cannot be absolutely guaranteed, the achievement of the required QoS through MAC scheduling has high probability. Moreover, PCPs 2 and 1 were mapped to QCI-7 and 6 with a looser but different Packet Delay Budget to achieve the required relative priority.
M4. The cyclic window time transmission principle by employing a TSN time-aware shaping scheduling algorithm and the nonpreemptive (NP) priority discipline were used to design an innovative time-aware shaping with relative priority (TAS-RP) scheduling algorithm to simultaneously achieve guaranteed and relative QoS.
The above innovative designs were integrated to implement an experimental platform (Scheduling eLAA for Wireless TSN, abbreviated ScheLAA-WTSN) for MAC QoS scheduling; the platform used eLAA to facilitate wireless networking between the work cell and the FM. Python was mainly used to develop the work cell and FM, then integrate a software-defined radio. The platform included an work cell controller emulator, eLAA-enabled TSN Switch & network emulator and factory management emulator which could be used for the development and experimentation of QoS-aware scheduling algorithms for supporting the work cell.
The main findings and contributions of this thesis are as follows. (1) Cell-level communication requirements in Process-automated SME factories were analyzed for a delay of about 60 ms in work instruction transmission, and the introduction of cell-level wireless communication was identified as one of the key requirements for the digital transformation of SME factories. (2) Wireless broadband communication between the FM and work cells in SME factories requires latency-guaranteed work instructions and warning latency lower than sensory data latency. LTE-, carrier aggregation-, and listen-before-talk-based technology-eLAA that can use both licensed and unlicensed spectra to support the TSN QoS required by SME factories should be chosen by cost-effectively using MAC layer LC scheduling. (3) The representative TSN QoS guaranteed and relative latency requirements should be chosen according to the cell-level communication considered, and mapped to the guaranteed and two relative quality QCIs to enable eLAA to handle the corresponding TSN QoS appropriately. (4) The proposed TAS-RP scheduling algorithm not only configures a periodic transmission period for PCP 4 owing to its periodic nature but also prioritizes PCP 2 over PCP 1 through the NP priority discipline in a non-PCP 4 transmission period. (5) On the basis of a simulation, it was found that in saturated traffic scenarios, TAS-RP could guarantee the PCP 4 packet delay and maintain the average latency of PCP 2 lower than PCP 1. Moreover, compared with the logical channel prioritization (LCP), the average latency of PCP 4 was reduced by about 2%–54%, and the ratio of PCP 2 packet delay lower than PCP 1 packet delay can be improved by up to about 68%. The proposed algorithm in this thesis can help simultaneously achieve the guaranteed and relative QoS for work cells in SME factories.

致謝 i
中文摘要 ii
Abstract v
List of Terms and Abbreviations x
Table of Contents xiii
List of Figures xvi
List of Tables xx
Chapter 1 Introduction 1
1.1 Motivation: Wireless Networking for Factories 1
1.2 Literature Review 2
1.3 Scope of Thesis 4
1.4 Organization of Thesis 5
Chapter 2 Framework of eLAA-enabled TSN for Work Cell-Factory Communications 6
2.1 Needs for Wireless Communications in a Smart SME Factory 6
2.1.1 Needs at Machine, Work Cell and Factory Levels 7
2.1.2 Traffic Characteristics and QoS Requirements for Work Cell 11
2.2 Wireless Enabler for Time Sensitive Network Switch between Work Cell and Factory 13
2.2.1 Time Sensitive Network (TSN) 14
2.2.2 TSN QoS Scheduling IEEE802.1Qbv (Time Aware Shaping) 16
2.3 eLAA as an Affordable Wireless Technology 17
2.3.1 LTE Enhanced Licensed Assisted Access (eLAA) 20
2.3.2 Carrier Aggregation between Licensed and Unlicensed Access 26
2.3.3 Channel Access Procedures in eLAA at MAC Layer 28
2.4 MAC Scheduling in eLAA 30
2.4.1 Resource Scheduling 30
2.4.2 Logical Channel Scheduling 31
2.4.3 eLAA QoS Architecture and Its Property 32
2.5 eLAA-enabled TSN Framework for Factory-Cell Communications 34
Chapter 3 QoS Mapping and Translator Design for Cell-level Communication 37
3.1 QoS Mapping Problem Definition and Challenges 37
3.1.1 Mapping of QoS between 3GPP eLAA and IEEE TSN 37
3.1.2 Challenges of QoS Class Mapping between 3GPP lea and IEEE TSN 38
3.1.3 Assumptions 39
3.2 QoS Mapping between TSN and eLAA for Cell-Level Communication Use Case 40
3.2.1 Design of QoS Mapping Principle 40
3.2.2 Mapping Table for Work Cell-Factory Use Case 42
3.3 TSN Translator Design 43
3.3.1 End-to-End (E2E) QoS Control in eLAA 43
3.3.2 Proposed TSN Translator (TTxl) Protocol Stack and Function in UE 44
3.3.3 Procedures for QoS Mapping and Control by TSN Translator 45
3.4 Summary 47
Chapter 4 Scheduling eLAA in MAC Layer 48
4.1 Scheduling Problem: Definition and Challenges 48
4.1.1 Scheduling Transmission of Logical Channels 48
4.1.2 Challenges in eLAA MAC Scheduling for TSN QoS 50
4.1.3 Assumptions 50
4.2 Priority Queue Model of Hybrid Traffic from Cell Controller 52
4.3 Algorithm Design: Time-Aware Shaping with Relative Priority (TAS-RP) 59
4.3.1 TAS-RP Ideas 59
4.3.2 TAS-RP Algorithm 61
4.3.3 Analysis of Guaranteed Latency for TAS-RP 63
4.4 Evaluation of TAS-RP Scheduling Performance 65
4.4.1 Parameter Setting and Test Scenarios 65
4.4.2 Metrics for QoS Awareness Evaluation 67
4.4.3 Guaranteed Latency and Relative Priority under Differently Total Traffic 67
4.4.4 Sensory Data Throughput Increase by Using Unlicensed Band 74
4.5 Summary 76
Chapter 5 Platform Implementation: ScheLAA-WTSN 77
5.1 Platform Overview 77
5.2 User Interface Design 84
5.2.1 Cell Controller UI 84
5.2.2 USRP UI 85
5.2.3 MEC UI 88
5.3 Platform Operation Procedures 90
5.4 Demonstration 92
5.4.1 Scenario I: Guaranteed Latency and Relative Priority under Different Traffic Conditions 92
5.4.2 Scenario II: Increased Capacity via Joint Utilization of Unlicensed Band 96
Chapter 6 Conclusions and Future Work 101
6.1 Conclusions 101
6.2 Future Work 103
Appendix 104
Bibliography 108

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