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    ETSI GR ENI 001-2018 Experiential Networked Intelligence (ENI) ENI use cases (V1 1 1).pdf

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    ETSI GR ENI 001-2018 Experiential Networked Intelligence (ENI) ENI use cases (V1 1 1).pdf

    1、 ETSI GR ENI 001 V1.1.1 (2018-04) Experiential Networked Intelligence (ENI); ENI use cases Disclaimer The present document has been produced and approved by the Experiential Networked Intelligence (ENI) ETSI Industry Specification Group (ISG) and represents the views of those members who participate

    2、d in this ISG. It does not necessarily represent the views of the entire ETSI membership. GROUP REPORT ETSI ETSI GR ENI 001 V1.1.1 (2018-04)2 Reference DGR/ENI-001 Keywords artificial intelligence, management, network, use case ETSI 650 Route des Lucioles F-06921 Sophia Antipolis Cedex - FRANCE Tel.

    3、: +33 4 92 94 42 00 Fax: +33 4 93 65 47 16 Siret N 348 623 562 00017 - NAF 742 C Association but non lucratif enregistre la Sous-Prfecture de Grasse (06) N 7803/88 Important notice The present document can be downloaded from: http:/www.etsi.org/standards-search The present document may be made avail

    4、able in electronic versions and/or in print. The content of any electronic and/or print versions of the present document shall not be modified without the prior written authorization of ETSI. In case of any existing or perceived difference in contents between such versions and/or in print, the only

    5、prevailing document is the print of the Portable Document Format (PDF) version kept on a specific network drive within ETSI Secretariat. Users of the present document should be aware that the document may be subject to revision or change of status. Information on the current status of this and other

    6、 ETSI documents is available at https:/portal.etsi.org/TB/ETSIDeliverableStatus.aspx If you find errors in the present document, please send your comment to one of the following services: https:/portal.etsi.org/People/CommiteeSupportStaff.aspx Copyright Notification No part may be reproduced or util

    7、ized in any form or by any means, electronic or mechanical, including photocopying and microfilm except as authorized by written permission of ETSI. The content of the PDF version shall not be modified without the written authorization of ETSI. The copyright and the foregoing restriction extend to r

    8、eproduction in all media. ETSI 2018. All rights reserved. DECTTM, PLUGTESTSTM, UMTSTMand the ETSI logo are trademarks of ETSI registered for the benefit of its Members. 3GPPTM and LTETMare trademarks of ETSI registered for the benefit of its Members and of the 3GPP Organizational Partners. oneM2M lo

    9、go is protected for the benefit of its Members. GSMand the GSM logo are trademarks registered and owned by the GSM Association. ETSI ETSI GR ENI 001 V1.1.1 (2018-04)3 Contents Intellectual Property Rights 6g3Foreword . 6g3Modal verbs terminology 6g31 Scope 7g32 References 7g32.1 Normative references

    10、 . 7g32.2 Informative references 7g33 Definitions and abbreviations . 7g33.1 Definitions 7g33.2 Abbreviations . 8g34 Overview 9g34.1 Background 9g34.2 Overview of the ENI System 9g34.2.1 Brief Description 9g34.2.2 Expected Benefits . 10g35 General use cases . 10g35.1 Introduction 10g35.2 Infrastruct

    11、ure Management 11g35.2.1 Use Case #1-1: Policy-driven IDC Traffic Steering . 11g35.2.1.1 Use case context 11g35.2.1.2 Description of the use case 11g35.2.1.2.1 Overview . 11g35.2.1.2.2 Motivation . 12g35.2.1.2.3 Actors and Roles 13g35.2.1.2.4 Initial context configuration 13g35.2.1.2.5 Trigger condi

    12、tions . 13g35.2.1.2.6 Operational Flow of the actions . 13g35.2.1.2.7 Post-conditions 14g35.2.2 Use Case #1-2: Handling of Peak Planned Occurrences. 14g35.2.2.1 Use case context 14g35.2.2.2 Description of the use case 14g35.2.2.2.1 Overview . 14g35.2.2.2.2 Motivation . 15g35.2.2.2.3 Actors and Roles

    13、 15g35.2.2.2.4 Initial context configuration 15g35.2.2.2.5 Triggering conditions 15g35.2.2.2.6 Operational flow of actions . 15g35.2.2.2.7 Post-conditions 16g35.2.3 Use Case #1-3: Energy optimization using AI 16g35.2.3.1 Use case context 16g35.2.3.2 Description of the use case 16g35.2.3.2.1 Overview

    14、 . 16g35.2.3.2.2 Motivation . 17g35.2.3.2.3 Actors and Roles 17g35.2.3.2.4 Initial context configuration 17g35.2.3.2.5 Triggering conditions 18g35.2.3.2.6 Operational flow of actions . 18g35.2.3.2.7 Post-conditions 18g35.3 Network Operations . 19g35.3.1 Use Case #2-1: Policy-driven IP managed networ

    15、ks 19g35.3.1.1 Use case context 19g35.3.1.2 Description of the use case 19g35.3.1.2.1 Overview . 19g35.3.1.2.2 Motivation . 19g3ETSI ETSI GR ENI 001 V1.1.1 (2018-04)4 5.3.1.2.3 Actors and Roles 20g35.3.1.2.4 Initial context configuration 20g35.3.1.2.5 Triggering conditions 20g35.3.1.2.6 Operational

    16、flow of actions . 20g35.3.1.2.7 Post-conditions 21g35.3.2 Use Case #2-2: Radio Coverage and capacity optimization . 21g35.3.2.1 Use case context 21g35.3.2.2 Description of the use case 21g35.3.2.2.1 Overview . 21g35.3.2.2.2 Motivation . 22g35.3.2.2.3 Actors and Roles 22g35.3.2.2.4 Initial context co

    17、nfiguration 22g35.3.2.2.5 Triggering conditions 22g35.3.2.2.6 Operational flow of actions . 22g35.3.2.2.7 Post-conditions 23g35.3.3 Use Case #2-3: Intelligent Software Rollouts . 23g35.3.3.1 Use Case context . 23g35.3.3.2 Description of the Use Case 23g35.3.3.2.1 Overview . 23g35.3.3.2.2 Motivation

    18、. 23g35.3.3.2.3 Actors and Roles 24g35.3.3.2.4 Initial context configuration 24g35.3.3.2.5 Triggering conditions 24g35.3.3.2.6 Operational flow of actions . 24g35.3.3.2.7 Post-conditions 25g35.3.4 Use Case #2-4: Policy-based network slicing for IoT security . 25g35.3.4.1 Use Case context . 25g35.3.4

    19、.2 Description of the Use Case 26g35.3.4.2.1 Motivation . 26g35.3.4.2.2 Actors and Roles 26g35.3.4.2.3 Initial context configuration 26g35.3.4.2.4 Triggering conditions 27g35.3.4.2.5 Operational flow of actions . 27g35.3.4.2.6 Post-conditions 27g35.3.5 Use Case #2-5: Intelligent Fronthaul Management

    20、 and Orchestration . 27g35.3.5.1 Use Case context . 27g35.3.5.2 Description of the use case 28g35.3.5.2.1 Overview . 28g35.3.5.2.2 Motivation . 28g35.3.5.2.3 Actors and Roles 29g35.3.5.2.4 Initial context configuration 29g35.3.5.2.5 Triggering conditions 29g35.3.5.2.6 Operational flow of actions . 2

    21、9g35.3.5.2.7 Post-conditions 29g35.4 Service Orchestration and Management . 29g35.4.1 Use Case #3-1: Context-aware VoLTE Service Experience Optimization . 29g35.4.1.1 Use case context 29g35.4.1.2 Description of the use case 30g35.4.1.2.1 Overview . 30g35.4.1.2.2 Motivation . 30g35.4.1.2.3 Actors and

    22、 Roles 30g35.4.1.2.4 Initial context configuration 31g35.4.1.2.5 Triggering conditions 31g35.4.1.2.6 Operational flow of actions . 31g35.4.1.2.7 Post-conditions 31g35.4.2 Use Case #3-2: Intelligent network slicing management 31g35.4.2.1 Use case context 31g35.4.2.2 Description of the use case 31g35.

    23、4.2.2.1 Overview . 31g35.4.2.2.2 Motivation . 32g35.4.2.2.3 Actors and Roles 32g35.4.2.2.4 Initial context configuration 33g3ETSI ETSI GR ENI 001 V1.1.1 (2018-04)5 5.4.2.2.5 Triggering conditions 33g35.4.2.2.6 Operational flow of actions . 33g35.4.2.2.7 Post-conditions 33g35.4.3 Use Case #3-3: Intel

    24、ligent carrier-managed SD-WAN . 33g35.4.3.1 Use case context 33g35.4.3.2 Description of the use case 34g35.4.3.2.1 Overview . 34g35.4.3.2.2 Motivation . 34g35.4.3.2.3 Actors and Roles 35g35.4.3.2.4 Initial context configuration 35g35.4.3.2.5 Triggering conditions 35g35.4.3.2.6 Operational flow of ac

    25、tions . 35g35.4.3.2.7 Post-conditions 36g35.5 Assurance . 36g35.5.1 Use Case #4-1: Network fault identification and prediction . 36g35.5.1.1 Use case context 36g35.5.1.2 Description of the use case 36g35.5.1.2.1 Overview . 36g35.5.1.2.2 Motivation . 37g35.5.1.2.3 Actors and Roles 37g35.5.1.2.4 Initi

    26、al context configuration 37g35.5.1.2.5 Triggering conditions 37g35.5.1.2.6 Operational flow of actions . 37g35.5.1.2.7 Post-conditions 37g35.5.2 Use Case #4-2: Assurance of Service Requirements 38g35.5.2.1 Use Case context . 38g35.5.2.2 Description of the Use Case 38g35.5.2.2.1 Overview . 38g35.5.2.

    27、2.2 Motivation . 39g35.5.2.2.3 Actors and Roles 39g35.5.2.2.4 Initial context configuration 40g35.5.2.2.5 Triggering conditions 40g35.5.2.2.6 Operational flow of actions . 40g35.5.2.2.7 Post-conditions 40g36 Recommendations to ENI 40g3Annex A: Bibliography 41g3Annex B: Authors Essential, or potentia

    28、lly Essential, IPRs notified to ETSI in respect of ETSI standards“, which is available from the ETSI Secretariat. Latest updates are available on the ETSI Web server (https:/ipr.etsi.org/). Pursuant to the ETSI IPR Policy, no investigation, including IPR searches, has been carried out by ETSI. No gu

    29、arantee can be given as to the existence of other IPRs not referenced in ETSI SR 000 314 (or the updates on the ETSI Web server) which are, or may be, or may become, essential to the present document. Trademarks The present document may include trademarks and/or tradenames which are asserted and/or

    30、registered by their owners. ETSI claims no ownership of these except for any which are indicated as being the property of ETSI, and conveys no right to use or reproduce any trademark and/or tradename. Mention of those trademarks in the present document does not constitute an endorsement by ETSI of p

    31、roducts, services or organizations associated with those trademarks. Foreword This Group Report (GR) has been produced by ETSI Industry Specification Group (ISG) Experiential Networked Intelligence (ENI). Modal verbs terminology In the present document “should“, “should not“, “may“, “need not“, “wil

    32、l“, “will not“, “can“ and “cannot“ are to be interpreted as described in clause 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. ETSI ETSI GR ENI 001 V1.1.1 (2018-04)7 1 Sco

    33、pe The present document includes a collection of use cases from a variety of stakeholders, where the use of an Experiential Networked Intelligence (ENI) system can be applied to the fixed network, the mobile network, or both, to enhance the operator experience through the use of network intelligence

    34、. 2 References 2.1 Normative references Normative references are not applicable in the present 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 vers

    35、ion applies. For non-specific references, the latest version of the referenced document (including 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

    36、 not necessary for the application of the present document but they assist the user with regard to a particular subject area. i.1 NGMN Alliance, Description of Network Slicing Concept, Version 1.0, January 13, 2016. NOTE: Available at https:/www.ngmn.org/fileadmin/user_upload/160113_Network_Slicing_

    37、v1_0.pdf. i.2 3GPP TR 23.799: “3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Study on Architecture for Next Generation System, 3GPP TR 23.799, V14.0.0, Release 14“, December 2016. i.3 5G Service-Guaranteed Network Slicing White Paper, Issue 1, March 2

    38、017.g3NOTE: Available at http:/ i.4 A. Morton, AT Universal Mobile Telecommunications System (UMTS); LTE; Telecommunication management; Principles and high level requirements (3GPP TS 32.101 version 11.4.0 Release 11)“. i.6 ETSI GS ENI 002 (V1.1.1): “Experiential Networked Intelligence (ENI); Requir

    39、ements“. i.7 ETSI GS ENI 005: “Experiential Networked Intelligence (ENI); Architecture“. i.8 ETSI GR ENI 004: “Experiential Networked Intelligence (ENI); Terminology“. 3 Definitions and abbreviations 3.1 Definitions For the purposes of the present document, the terms and definitions given in ETSI GR

    40、 ENI 004 i.8 apply. ETSI ETSI GR ENI 001 V1.1.1 (2018-04)8 3.2 Abbreviations For the purposes of the present document, the following abbreviations apply: AI Artificial Intelligence AP Access Point API Application Programming Interface BBU Baseband Unit BRAS Broadband Remote Access Server BSS Busines

    41、s Support System CCO Capacity and Coverage Optimization CGN Carrier Grade Network address translation CPRI Common Public Radio Interface CPU Computing Processing Unit C-RAN Centralized RAN DC Data Centre DDOS Distributed Denial Of Service DHCP Dynamic Host Configuration Protocol D-RAN Distributed RA

    42、NE2E End-to-End ENI Experiential Networked Intelligence FTP File Transfer Protocol IDC Internet Data Centre INFP Intelligent Network Failure Prevention IP Internet Protocol KPI Key Performance Indicator MANO Management and Orchestration MEC Multi-access Edge Computing MIMO Multiple Input Mutliple Ou

    43、tput MPLS Multi-Protocol Label Switching NFV Network Function Virtualisation NFVI NFV Infrastructure NGFI Next Generation Fronthaul interface NGMN Next Generation Mobile Networks NSI Network Slice Instances OPEX OPerational EXpenditure OS Operating Systems OSS Operations Support System PHY PHYsical

    44、layer QoE Quality-of-Experience QoS Quality-of-Service RAM Random Access Memory RAN Radio Access Network RAU Remote Aggregation Unit RCC Radio Cloud Centre RF Radio Frequency RRU Remote Radio Units RSRP Reference Signal Received Power SDN Software Defined Networking SD-WAN Software-Defined Wide Area

    45、 Network SLA Service-Level Agreement TCP Transmission Control Protocol UE User EquipmentVM Virtual Machines VNF Virtualised Network Functions WAN Wireless Access Network WLAN Wireless Local Area Network ETSI ETSI GR ENI 001 V1.1.1 (2018-04)9 4 Overview 4.1 Background Operators see human-machine inte

    46、raction as slow, error-prone, expensive, and cumbersome. For example, operators are worried about the increasing complexity of integration of different standardization platforms in their network and operational environment; this is due to the vast differences inherent in programming different device

    47、s as well as the difficulty in building agile, personalized services that can be easily created and torn down. These human-machine interaction challenges are considered by operators as barriers to reducing the time to market of innovative and advanced services. Moreover, there is no efficient and ex

    48、tensible standards-based mechanism to provide contextually-aware services (e.g. services that adapt to changes in user needs, business goals, or environmental conditions). These and other factors contribute to a very high OPerational EXpenditure (OPEX) for network management. Operators need the abil

    49、ity to automate their network configuration and monitoring processes to reduce OPEX. More importantly, operators need to improve the use and maintenance of their networks. In particular, this requires the ability to visualize services and their underlying operations so that the proper changes can be applied to protect offered services and resources (e.g. ensure that their Quality-of-Service (QoS) and Quality-of-Experience (QoE) requirements are not vi


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