1、 ETSI TR 103 529 V1.1.1 (2018-08) SmartM2M; IoT over Cloud back-ends: A Proof of Concept TECHNICAL REPORT ETSI ETSI TR 103 529 V1.1.1 (2018-08) 2 Reference DTR/SmartM2M-103529 Keywords cloud, IoT, open source, proof of concept, virtualisation ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cede
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8、ners. oneM2M logo is protected for the benefit of its Members. GSMand the GSM logo are trademarks registered and owned by the GSM Association. ETSI ETSI TR 103 529 V1.1.1 (2018-08) 3 Contents Intellectual Property Rights 5g3Foreword . 5g3Modal verbs terminology 5g3Introduction 5g31 Scope 7g32 Refere
9、nces 7g32.1 Normative references . 7g32.2 Informative references 7g33 Definitions and abbreviations . 7g33.1 Definitions 7g33.2 Abbreviations . 8g34 Virtualization of IoT: A Proof-of-Concept. 8g34.1 Virtualized IoT and Cloud-Native Computing . 8g34.2 The rationale for a Proof-of-Concept . 8g34.3 Con
10、tent of the report. 9g35 Main elements of the Proof-of-Concept . 9g35.1 The Use Case 9g35.2 High-Level Architecture . 10g35.3 Technical choices . 10g35.4 Message flow 11g35.5 Auto scaling up and down 12g36 Implementation . 12g36.1 Initial Deployment architecture 12g36.2 Set-up of the PoC Deployment
11、Infrastructure 13g36.2.1 Installation of the Kubernetes cluster 13g36.2.1.1 Introduction . 13g36.2.1.2 Utilization of GoogleTMCloud Kubernetes Engine . 13g36.2.1.3 Installation from scratch 14g36.2.2 Installation of the IoT Components 17g36.2.3 Horizontal autoscaling 18g37 Conclusions 19g37.1 Introd
12、uction 19g37.2 Lessons Learned and Recommendations 19g3Annex A: Change History . 20g3History 21g3ETSI ETSI TR 103 529 V1.1.1 (2018-08) 4 List of figures Figure 1: PoC High level architecture .10g3Figure 2: Open source components in the Proof-of-Concept 11g3Figure 3: Message Flow in the Proof-of-Conc
13、ept .11g3Figure 4: Kubernetes Horizontal Pod Autoscaler (HPA) architecture 12g3Figure 5: PoC initial deployment architecture .13g3ETSI ETSI TR 103 529 V1.1.1 (2018-08) 5 Intellectual Property Rights Essential patents IPRs essential or potentially essential to normative deliverables may have been dec
14、lared to ETSI. The information pertaining to these essential IPRs, if any, is publicly available for ETSI members and non-members, and can be found in ETSI SR 000 314: “Intellectual Property Rights (IPRs); Essential, or potentially Essential, IPRs notified to ETSI in respect of ETSI standards“, whic
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18、eword This Technical Report (TR) has been produced by ETSI Technical Committee Smart Machine-to-Machine communications (SmartM2M). Modal verbs terminology In the present document “should“, “should not“, “may“, “need not“, “will“, “will not“, “can“ and “cannot“ are to be interpreted as described in c
19、lause 3.2 of the ETSI Drafting Rules (Verbal forms for the expression of provisions). “must“ and “must not“ are NOT allowed in ETSI deliverables except when used in direct citation. Introduction In addition to interoperability and security that are two recognized key enablers to the development of l
20、arge IoT systems, a new one is emerging as another key condition of success: virtualization. The deployment of IoT systems will occur not just within closed and secure administrative domains but also over architectures that support the dynamic usage of resources that are provided by virtualization t
21、echniques over cloud back-ends. This new challenge for IoT requires that the elements of an IoT system can work in a fully interoperable, secure and dynamically configurable manner with other elements (devices, gateways, storage, etc.) that are deployed in different operational and contractual condi
22、tions. To this extent, the current architectures of IoT will have to be aligned with those that support the deployment of cloud-based systems (private, public, etc.). Moreover, these architectures will have to support very diverse and often stringent non-functional requirements such as scalability,
23、reliability, fault tolerance, massive data, security. This will require very flexible architectures for the elements (e.g. the application servers) that will support the virtualized IoT services, as well as very efficient and highly modular implementations that will make a massive usage of Open Sour
24、ce components. These architectures and these implementations form a new approach to IoT systems and the solutions that this STF will investigate will also have to be validated: to this extent, a Proof-of-Concept implementation involving a massive number of virtualized elements will be made. ETSI ETS
25、I TR 103 529 V1.1.1 (2018-08) 6 The present document is one of three Technical Reports addressing this issue: ETSI TR 103 527 i.1: “SmartM2M; Virtualized IoT Architectures with Cloud Back-ends“. ETSI TR 103 528 i.2: “Landscape for open source and standards for cloud native software for a Virtualized
26、 IoT service layer“. ETSI TR 103 529 (the present document): “IoT over Cloud back-ends: A Proof of Concept“. ETSI ETSI TR 103 529 V1.1.1 (2018-08) 7 1 Scope The present document: Recalls the main elements of the Proof-of-Concept (PoC) in support of IoT Virtualization: use case description, high-leve
27、l architecture of the application developed, main technical choices. Presents the main implementation choices. Outlines the lessons learned and the possible impact of future IoT Virtualization implementations. 2 References 2.1 Normative references Normative references are not applicable in the prese
28、nt document. 2.2 Informative references References are either specific (identified by date of publication and/or edition number or version number) or non-specific. For specific references, only the cited version applies. For non-specific references, the latest version of the referenced document (inc
29、luding any amendments) applies. NOTE: While any hyperlinks included in this clause were valid at the time of publication, ETSI cannot guarantee their long term validity. The following referenced documents are not necessary for the application of the present document but they assist the user with reg
30、ard to a particular subject area. i.1 ETSI TR 103 527: “SmartM2M; Virtualized IoT Architectures with Cloud Back-ends“. i.2 ETSI TR 103 528: “SmartM2M; Landscape for open source and standards for cloud native software applicable for a Virtualized IoT service layer“. 3 Definitions and abbreviations 3.
31、1 Definitions For the purposes of the present document, the following terms and definitions apply: Open Source Software (OSS): computer software that is available in source code form NOTE: The source code and certain other rights normally reserved for copyright holders are provided under an open-sou
32、rce license that permits users to study, change, improve and at times also to distribute the software. source code: any collection of computer instructions written using some human-readable computer language, usually as text standard: output from an SSO ETSI ETSI TR 103 529 V1.1.1 (2018-08) 8 Standa
33、rds Setting Organization (SSO): any entity whose primary activities are developing, coordinating, promulgating, revising, amending, reissuing, interpreting or otherwise maintaining standards that address the interests of a wide base of users outside the standards development organization NOTE: In th
34、e present document, SSO is used equally for both Standards Setting Organization or Standards Developing Organizations (SDO). 3.2 Abbreviations For the purposes of the present document, the following abbreviations apply: API Application Programming Interface CPU Central Processing Unit CSE Common Ser
35、vice Entity (in oneM2M) CSP Cloud Service Provider EOF End Of File HLA High-Level Architecture HPA Horizontal Pod Autoscaler IaaS Infrastructure as a Service NFS Network File System OSS Open Source Software PaaS Platform as a Service PoC Proof of Concept RAM Random Access Memory RC Replication Contr
36、oller REST REpresentational State Transfer SaaS Software as a Service SDO Standards Development Organization SSH Secure SHell SSO Standards Setting Organization STF Specialist Task Force VM Virtual Machine YAML YAML Aint Markup Language 4 Virtualization of IoT: A Proof-of-Concept 4.1 Virtualized IoT
37、 and Cloud-Native Computing The IoT industry has started to understand and evaluate the potential benefits of Cloud-Native Computing for the fast, effective and future-safe development of IoT systems combining the strengths of both IoT and Cloud industries in a new value proposition. The expectation
38、 of Cloud-Native applications is to benefit from offerings from Cloud Service Providers (CSP) that may cover all or part of the layers of Virtualized application, via Infrastructure as a Service (IaaS), Platform as a Service (PaaS) or Software as a Service (SaaS). In the case of IoT applications, th
39、e trade-off between what is delegated to the Cloud Service Provider and what is kept in the hands of the application developers may vary depending a large number of potential factors and will finally materialize into different architecture, design and implementation choices. The approach of Cloud-Na
40、tive Computing is now widely supported by a large set of technologies embedded in Cloud-Native Infrastructures in support of Cloud-Native Applications. These technologies are now very diverse, technology-ready (as shown in the landscape of Open Source components described in ETSI TR 103 528 i.2) and
41、 support all the layers of a Micro-Service Architecture (such as the one described in ETSI TR 103 527 i.1). ETSI ETSI TR 103 529 V1.1.1 (2018-08) 9 4.2 The rationale for a Proof-of-Concept As pointed out in ETSI TR 103 527 i.1, “there is probably a large number of IoT Use Cases for which a “traditio
42、nal“ (i.e. non-virtualized) approach can and will apply. However, the introduction of IoT Virtualization is expected to make some Use Cases more effective: it would generally improve the efficiency of their implementation or support interoperability at a more fine-grained level (or both)“. The Cloud
43、-Native Computing technologies have been made much easier to apprehend, to master and to package into more and more complex systems. However, the effective usage of the vast catalogue of components potentially applicable for IoT Virtualization is still under evaluation in the IoT community. The Proo
44、f-of-concept (PoC) of IoT Virtualization exposed in the present report is an implementation of the “Horizontal Up and Down Auto-Scaling“ Use Case which has been selected in ETSI TR 103 527 i.1 as a well-adapted example for the following reasons: It demonstrates the feasibility of IoT Virtualization
45、on a “real-life“ Use Case applicable to a large number of sectors (aka “verticals“). It addresses a feature (auto-scaling) that is being deemed as very critical in virtualized IoT and for which an implementation via the use of “off-the-shelf“ Open Source Software components requires some validation.
46、 It makes use of a great number of the Open Source Software components described in ETSI TR 103 528 i.2. 4.3 Content of the report Clause 5 outlines the main elements for the definition, design and implementation of the selected Use Case, mostly the High-Level Architecture, the main Open Source comp
47、onents selected and the message flow. Clause 6 describes the initial deployment architecture and explains the steps to be followed for the set-up of the deployment infrastructure. Clause 7 outlines the main lessons learned from the implementation and provides a few basic recommendations. 5 Main elem
48、ents of the Proof-of-Concept 5.1 The Use Case The amount and type of data transmitted by IoT devices may vary drastically in time depending on some events that can be internal or external to the virtualized IoT system (e.g. road traffic increase during holiday departure). A cloud-native IoT platform
49、 will be able to continuously monitor its resources, scale-up its capabilities when needed, then scale-down to an optimized state to avoid wasting resources. This capability is referred to as “Auto-Scaling. The main objective of Auto Scaling is to ensure that the number of Virtual Machine (VM) instances available for and used by the virtualized application are optimal at a given time. Practically, a minimum number of VM instances is defined (lower threshold for the auto-scaling down) as well as a maximum number (upper threshold for the aut