An Efficient Data collection method for Digital Twin Network
draft-zhu-nmrg-digitaltwin-data-collection-01

Document Type Active Internet-Draft (individual)
Authors Yanhong Zhu  , Danyang Chen  , Cheng Zhou  , Pedro Martinez-Julia 
Last updated 2021-10-25
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Internet Research Task Force                                      Y. Zhu
Internet-Draft                                                   D. Chen
Intended status: Informational                                   C. Zhou
Expires: 28 April 2022                                      China Mobile
                                                  P. Martinez-Julia, Ed.
                                                                    NICT
                                                         25 October 2021

      An Efficient Data collection method for Digital Twin Network
             draft-zhu-nmrg-digitaltwin-data-collection-01

Abstract

   Digital Twin Network is a network system with Physical Network and
   Twin Network, which can be mapped interactively in real time.  The
   construction of Digital Twin Network requires real-time data of
   Physical Network to update the state of Twin Network.  However the
   existing method collects the full amount of data from the Physical
   Network for modeling, and does not consider the problems such as
   time-lag, insufficient storage resources, low computational
   efficiency and waste of bandwidth resources.  This document
   introduces an efficient data collection, aggregation and correlation
   method in which the Twin Network sends instructions to the Physical
   Network to collect data on demand, and then the Physical Network
   completes instructions such as knowledge representation, Telemetry
   Streaming Element of Physical Network completes data aggregation and
   correlation.  Finally Telemetry Streaming Element sends the processed
   data to the Twin Network.

Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
   document are to be interpreted as described in RFC 2119 [RFC2119].

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at https://datatracker.ietf.org/drafts/current/.

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   Internet-Drafts are draft documents valid for a maximum of six months
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   This Internet-Draft will expire on 28 April 2022.

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Definitions and Acroyms . . . . . . . . . . . . . . . . . . .   3
   3.  Overview  . . . . . . . . . . . . . . . . . . . . . . . . . .   3
   4.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .   7
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .   7
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .   8
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .   8
     7.2.  Informative References  . . . . . . . . . . . . . . . . .   8
   Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .   8
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .   8

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1.  Introduction

   With the deployment of Internet of Things, cloud computing and data
   center, etc., the scale of the current network is expanded gradually.
   However, the increase of network scale leads to the increasing
   complexity of the current network, and that induces plenty of
   problems.  In order to improve the autonomy ability of network and
   reduce the negative effect on Physical Network, we consider that an
   endogenous intelligent and autonomous network architecture which
   achieves self-optimization and decision is indispensable.  Digital
   twin, as an innovative technology, has the potential to realize this
   architecture because it can optimize and validate policies through
   real-time and interactive mapping with physical
   entities.[I-D.zhou-nmrg-digitaltwin-network-concepts]

   Data is the cornerstone of Digital Twin Network construction.  In the
   face of large network scale, data collection, storage and management
   are faced with great challenges.  If the full-data collection method
   is adopted, huge storage space and bandwidth resource is needed,
   especially for complex scenarios that require real-time data and
   traffic from multi-source heterogeneous devices.  Therefore, it is
   extremely important to propose a lightweight and efficient data
   collection, aggregation and correlation method.

2.  Definitions and Acroyms

   PN: Physical Network

   IMC: Instruction Management Center

   DSC: Data Storage Center

   TN: Twin Network

   TSE: Telemetry Streaming Element

   RDF: Resource Description Framework

   CPE: Complex Event Processing

3.  Overview

   Digital Twin Network is a network system with Physical Network and
   Twin Network, which can be mapped interactively in real time.  The
   construction of Digital Twin Network requires real-time data of
   Physical Network to update the state of Twin Network.  However the
   existing method collects the full amount of data from the Physical
   Network for modeling, and does not consider the problems such as

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   time-lag, insufficient storage resources, low computational
   efficiency and waste of bandwidth resources caused by data
   transmission.  In order to solve these problems, this memo introduces
   an efficient data collection method for Digital Twin Network.  This
   data collection method is to sends instructions model in the Twin
   Network to the Physical Network to collect data on demand, and then
   the Physical Network completes instructions such as data cleaning or
   knowledge representation, and then sends the representation data to
   the Digital Twin Network.

   Digital Twin Network consists of Physical Network and Twin Network.
   The Physical Network includes multiple Data Storage Centers and
   Telemetry Streaming Element[I-D.ietf-opsawg-ntf], and the Twin
   Network includes the Instruction Management Center and Data Storage
   Center.  Telemetry Streaming Element has multiple functions,
   including data collection, data aggregation, data correlation,
   knowledge representation and query, etc.  In addition, the Complex
   Event Processing(CPE) engineer is integrated into TSE to perform
   query function.  The Instruction Management has two functions.  On
   the one hand, the Instruction Management Center of the Twin Network
   is mainly used to manage the registration of the Data Storage Center
   in the Physical Network, and its registration information can include
   various key information such as the IP address of the Data Storage
   Center in the Physical Network, data type, and various index names in
   the data , data source name and data size, etc; on the other hand, it
   is mainly used to adaptively configure data collection instructions
   according to the collection requirements of the Data Storage Center
   in the Twin Network, and search for IP addresses to send
   instructions.  The instruction-carrying information includes rule-
   based mathematical expressions, executable models in .exe format,
   dynamic collection frequency, parameter lists, program text files in
   .m format, text files with parameter configuration, and other types
   of files.  Instructions are flexible and programmable, and can be
   created, modified, combined, and deleted at any time according to
   requirements.  When the Data Storage Center of the Twin Network
   initiates data collection requests to the Instruction Management
   Center, the Instruction Management Center searches for IP addresses
   of Data Storage Center from registration information according to
   critical information such as data type and data name, and functional
   instructions for data processing or knowledge representation can be
   implemented depending on the demand configuration.  The Data Storage
   Center of the Twin Network is mainly used to store the effective
   information after data processing and knowledge representation
   returned by the Telemetry Streaming Element in the Physical Network.

   Data Storage Center in the Physical Network has two functions.  On
   the one hand, it can store data, such as performance indicators,
   operational status, log, traffic scheduling, business requirements,

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   etc.  On the other hand, it has the function of automatically parsing
   the instructions sent by the Telemetry Streaming Element.  Then the
   operating environment of the instruction is configured according to
   the instruction needs, and data processing or knowledge
   representation is performed based on the instruction.  Data
   processing mainly includes data cleaning, filling missing data,
   normalization, conflict verification, etc.  Knowledge representation
   refers to the representation of the original data as a data structure
   that can be used for efficient computation.  Such representation
   results are closer to machine language, which is conducive to the
   rapid and accurate construction of the model.  The role of knowledge
   representation is to represent the original data as a data structure
   that can be used to efficiently calculate.  Such representation
   results closer to the machine language, which is conducive to the
   rapid and accurate construction of the model.

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   +------------------------------+   +-----------------------+
   |   Physical  Network          |   |  Digital Twin Network |
   | +-----+    +-----+  +------+ |   |  +------+  +-------+  |
   | |     |    |     |  |      | |   |  |      |  |       |  |
   | | DSC |... | DSC |  | TSE  | |   |  |  IMC |  |  DSC  |  |
   | |     |    |     |  |      | |   |  |      |  |       |  |
   | +-+---+    +--+--+  +---+--+ |   |  +---+--+  +----+--+  |
   |   |           |         |    |   |      |          |     |
   +------------------------------+   +-----------------------+
       |           |         |               |          |
       | 1.1register         |               |          |
       +-----------+--------->               |          |
       |           |         |               |          |
       |           |1.2register              |          |
       |           +--------->               |          |
       |           |         | 1.3register   |          |
       |           |         +--------------->          |
       |           |         |            2.data request|
       |           |         |               <----------+
       |           |         |   3.query and instruction|
       |           |         |   configuration          |
       |           |         |               |          |
       |           |         4.send instruction         |
       |           |         <---------------+          |
       |           |         |               |          |
       |           |   5.parse and execute   |          |
       |           |       instruction       |          |
       |  6.data subscription|               |          |
       <---------------------+               |          |
       | 7.knowledge         |               |          |
       | representation      |               |          |
       |    8.data pushing   |               |          |
       +--------------------->               |          |
       |           |  9.data aggregation and |          |
       |           |     correlation         |          |
       |           |         |10.send processed data    |
       |           |         +-------------------------->
       |           |         |               |          |

   The specific process is as follows:

   *  The Data Storage Centers in the Physical Network registers with
      the Telemetry Streaming Element in the Physical Network.  The
      Telemetry Streaming Element registers with the Instruction
      management center.  The registration information includes the IP
      address of the Data Storage Center, the data type, the data
      source, or the data size, etc.

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   *  The Data Storage Center in the Twin Network sends the data
      collection request to the Instruction Management Center.

   *  According to the data collection request, the Instruction
      Management Center intelligently query the registration information
      for addressing, and configures the data processing instruction.

   *  The Instruction Management Center in the Twin Network sends the
      corresponding instruction according to the query result to the
      Telemetry Streaming Element in the Physical Network.

   *  After receiving the instructions, the Telemetry Streaming Element
      in the Physical Network will parse them and execute them according
      to the instructions, and query the location of data stored.  The
      query function can be performed by the Complex Event Processing
      (CEP) engine, which receives all telemetry data and processes it
      with all queries provided.

   *  The Telemetry Streaming Element sends data subscription to DSC of
      the Physical Network.

   *  DSC of Physical Network performs knowledge representation of local
      data, for example, in RDF form, also sends raw data to TSE for
      knowledge representation.

   *  DSC of Physical Network push data or knowledge to TSE.

   *  TSE aggregates and correlates the collected data or knowledge.
      Then according to the actual needs, decide whether to perform
      knowledge representation.

   *  TSE sends the processed data or knowledge to DSC of Twin Network.

4.  Conclusion

   This memo introduces an efficient data collection method for Digital
   Twin Network.  This data collection method is to sends instructions
   model in the Twin Network to the Physical Network to collect data on
   demand, and then the Physical Network completes instructions such as
   data cleaning or knowledge representation, and then sends the
   representation data to the Digital Twin Network.  And the data
   collection process between the Physical Network and the Twin Network
   is introduced in detail.

5.  Security Considerations

   TBD.

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6.  IANA Considerations

   This document has no requests to IANA.

7.  References

7.1.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,
              <https://www.rfc-editor.org/info/rfc2119>.

7.2.  Informative References

   [I-D.ietf-opsawg-ntf]
              Song, H., Qin, F., Martinez-Julia, P., Ciavaglia, L., and
              A. Wang, "Network Telemetry Framework", Work in Progress,
              Internet-Draft, draft-ietf-opsawg-ntf-09, 13 October 2021,
              <https://www.ietf.org/archive/id/draft-ietf-opsawg-ntf-
              09.txt>.

   [I-D.zhou-nmrg-digitaltwin-network-concepts]
              Zhou, C., Yang, H., Duan, X., Lopez, D., Pastor, A., Wu,
              Q., Boucadair, M., and C. Jacquenet, "Digital Twin
              Network: Concepts and Reference Architecture", Work in
              Progress, Internet-Draft, draft-zhou-nmrg-digitaltwin-
              network-concepts-04, 7 July 2021,
              <https://www.ietf.org/archive/id/draft-zhou-nmrg-
              digitaltwin-network-concepts-04.txt>.

Index

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      ?

         ???
            Section 3

Authors' Addresses

   Yanhong Zhu
   China Mobile
   Beijing
   100053
   China

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   Email: zhuyanhong@chinamobile.com

   Danyang Chen
   China Mobile
   Beijing
   100053
   China

   Email: chendanyang@chinamobile.com

   Cheng Zhou
   China Mobile
   Beijing
   100053
   China

   Email: zhouchengyjy@chinamobile.com

   Pedro Martinez-Julia (editor)
   NICT
   4-2-1, Nukui-Kitamachi, Koganei, Tokyo,
   184-8795
   Japan

   Email: pedro@nict.go.jp

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