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YANG model for finite state machine
draft-sambo-netmod-yang-fsm-02

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This is an older version of an Internet-Draft whose latest revision state is "Expired".
Authors Nicola Sambo , Piero Castoldi , Giuseppe Fioccola , Filippo Cugini , Haoyu Song , Tianran Zhou
Last updated 2018-03-02
Replaces draft-sambo-opsawg-ccamp-supa-ext-yang-fsm
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draft-sambo-netmod-yang-fsm-02
NETMOD Working Group                                            N. Sambo
Internet-Draft                                               P. Castoldi
Intended status: Standards Track              Scuola Superiore Sant'Anna
Expires: September 3, 2018                                   G. Fioccola
                                                          Telecom Italia
                                                               F. Cugini
                                                                    CNIT
                                                                 H. Song
                                                                 T. Zhou
                                                                  Huawei
                                                           March 2, 2018

                  YANG model for finite state machine
                     draft-sambo-netmod-yang-fsm-02

Abstract

   Network operators and service providers are facing the challenge of
   deploying systems from different vendors while looking for a trade-
   off among transmission performance, network device reuse, and capital
   expenditure without the need of being tied to single vendor
   equipment.  The deployment and operation of more dynamic and
   programmable network infrastructures can be driven by adopting model-
   driven and software-defined control and management paradigms.  In
   this context, YANG enables to compile a set of consistent vendor-
   neutral data models for networks and components based on actual
   operational needs emerging from heterogeneous use cases.  This
   document proposes YANG models to describe events, operations, and
   finite state machine of YANG-defined network elements.  The proposed
   models can be applied in several use cases: i) in the context of
   optical networks to pre-instruct data plane devices (e.g., an optical
   transponder) on the actions to be performed (e.g., code adaptation)
   in case some events, such as physical layer degradations, occur; ii)
   in general data networks, network telemetry applications can define
   and embed custom data probes into data plane devices.  A probe in
   many cases can be modeled as an FSM; iii) the monitoring of packet
   loss and delay through a network clustering approach.

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
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on September 3, 2018.

Copyright Notice

   Copyright (c) 2018 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
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   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Conventions used in this document . . . . . . . . . . . . . .   3
   3.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Example of application  . . . . . . . . . . . . . . . . . . .   4
     4.1.  Pre-programming resiliency schemes in EONs  . . . . . . .   4
     4.2.  Deploying Dynamic Probes for Programmable Network
           Telemetry . . . . . . . . . . . . . . . . . . . . . . . .   7
     4.3.  IP Performance Measurements on multipoint-to-multipoint
           large Networks  . . . . . . . . . . . . . . . . . . . . .   9
   5.  YANG for finite state machine (FSM) . . . . . . . . . . . . .  10
   6.  Implementation of the pre-programming resiliency schemes in
       EONs  . . . . . . . . . . . . . . . . . . . . . . . . . . . .  13
   7.  Appendix  . . . . . . . . . . . . . . . . . . . . . . . . . .  14
     7.1.  YANG model for FSM - Tree . . . . . . . . . . . . . . . .  14
     7.2.  YANG model for FSM - Code . . . . . . . . . . . . . . . .  15
     7.3.  Example of values for the YANG model  . . . . . . . . . .  27
   8.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  28
   9.  Other Contributors  . . . . . . . . . . . . . . . . . . . . .  28
   10. Security Considerations . . . . . . . . . . . . . . . . . . .  29
   11. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  29
   12. References  . . . . . . . . . . . . . . . . . . . . . . . . .  29
     12.1.  Normative References . . . . . . . . . . . . . . . . . .  29
     12.2.  Informative References . . . . . . . . . . . . . . . . .  29
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  30

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1.  Introduction

   Networks are evolving toward more programmability, flexibility, and
   multi-vendor interoperability.  Multi-vendor interoperability can be
   applied in the context of nodes, i.e. a node composed of components
   provided by different vendors (named fully disaggregated white box)
   is assembled under the same control system.  This way, operators can
   optimize costs and network performance without the need of being tied
   to single vendor equipment.  NETCONF protocol RFC6241 [RFC6241] based
   on YANG data modeling language RFC6020 [RFC6020] is emerging as a
   candidate Software Defined Networking (SDN) enabled protocol.  First,
   NETCONF supports both control and management functionalities, thus
   permits high programmability.  Then, YANG enables data modeling in a
   vendor-neutral way.  Some recent works have provided YANG models to
   describe attributes of links (e.g., identification), nodes (e.g.,
   connectivity matrix), media channels, and transponders (e.g.,
   supported forward error correction - FEC) of networks
   ([I-D.ietf-i2rs-yang-network-topo] [I-D.vergara-ccamp-flexigrid-yang]
   [I-D.zhang-ccamp-l1-topo-yang]), also including optical technologies.
   This document presents YANG models to describe events, operations,
   and finite state machine of YANG-defined network elements.  Such
   models can be applied to several use cases.  In the context of
   elastic optical networks (EONs), the model enables a centralized
   remote network controller (managed by a network operator) to instruct
   a transponder controller about the actions to perform when certain
   events (e.g., failures) occur.  The actions to be taken and the
   events can be re-programmed on the device.  In general data networks,
   programmable network telemetry is considered a killer SDN application
   which can help applications gain unprecedented visibility to network
   data plane.  Instead of providing raw data, network devices can be
   configured to filter and process data directly on the data plane and
   only hand preprocessed data to the collector, in order to save data
   bandwidth and reduce reaction delay ([I-D.song-opsawg-dnp4iq]) . Such
   configurations can be programed as custom probes and dynamically
   deployed into data plane devices.  A probe in many cases can be
   modeled as an FSM.  Another use case is the monitoring of packet loss
   and delay through a network clustering approach: in this case, each
   FSM state is determined by a specific subdivision of the network in
   Clusters ([I-D.fioccola-ippm-multipoint-alt-mark]).

2.  Conventions used in this document

   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 RFC2119 [RFC2119].

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3.  Terminology

   ABNO: Application-Based Network Operations

   BER: Bit Error Rate

   EON: Elastic Optical Network

   FEC: Forward Error Correction

   FSM: Finite State Machine

   NETCONF: Network Configuration Protocol

   OAM: Operation Administration and Maintenance

   SDN: Software Defined Network

   YANG: Yet Another Network Generator

   DNP: Dynamic Network Probe

   AMM: Alternate Marking Method

4.  Example of application

4.1.  Pre-programming resiliency schemes in EONs

   EONs (optical networks based on flexible grid supporting circuits of
   different bandwidth) are expected to employ flexible transponders,
   i.e. transponders supporting multiple bit rates, multiple modulation
   formats, and multiple codes.  Such transponders permits the (re-)
   configuration of the bit rate value based on traffic requirements, as
   well as the configuration of the modulation format and code based on
   the physical characteristics of a path (e.g., quadrature phase shift
   keying is more robust than 16 quadrature amplitude modulation).  This
   way, transmission parameters can be (re-) configured based on
   physical layer changes.  The YANG model presented in this draft
   enables to pre-program reconfiguration settings of data plane devices
   in case of failures or physical layer degradations.  In particular,
   soft failures are assumed.  Soft failures imply transmission
   performance degradation, in turns a bit error rate (BER) increase,
   e.g. due to the ageing of some network devices.  Without loosing
   generality, the ABNO architecture is assumed for the control and
   management of EONs (RFC7491 [RFC7491]).  Considering the state of the
   art, when pre-FEC BER passes above a predefined threshold, it is
   expected that an alarm is sent to the OAM Handler, which communicates
   with the ABNO controller that may trigger an SDN controller (that

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   could be the Provisioning Manager of ABNO RFC7491 [RFC7491]) for
   computing new transmission parameters.  The involved ABNO modules are
   shown in the simplified ABNO architecture of Fig. 1.  Then,
   transponders are reconfigured.  When alarms related to several
   connections impacted by the soft failure are generated, this
   procedure may be particularly time consuming.  The related workflow
   for transponder reconfiguration is shown in Fig. 2.  The proposed
   model enables an SDN controller to instruct the transponder about
   reconfiguration of new transmission parameters values if a soft
   failure occurs.  This can be done before the failure occurs (e.g.,
   during the connection instantiation phase or during the connection
   service), so that data plane devices can promptly reconfigure
   themselves without querying the SDN controller to trigger an on-
   demand recovery.  This is expected to speed up the recovery process
   from soft failures.  The related flow chart is shown in Fig. 3.

          ___________            ___________
         |  ABNO     |          |   OAM     |
         |controller |  ------  |  Handler  |
         |___________|          |___________|

           |                         |
           |                         |
           |                         |
        ____________                 |
       |    SDN     |                |
       | controller |                |
       |____________|                |
                                     |
            |                        |
            |                        |
            |                        |
          _____________________________
         |            Client           |
         |            network          |
         |_____________________________|

                 Figure 1: Assumed ABNO functional modules

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              _____________________
             |         1           |
             |Sending alarm to the |
             |     OAM Handler     |
             |                     |
             |_____________________|
                       |
                       |
                       |
             _____________________
            |          2          |
            |       Trigger       |
            |    SDN Controller   |
            |                     |
            |_____________________|
                       |
                       |
                       |
             _____________________
            |          3          |
            |   Computation of    |
            |  new transmission   |
            |    parameters       |
            |_____________________|
                      |
                      |
                      |
             _____________________
            |         4           |
            |    Data plane       |
            |    reconfiguration  |
            |                     |
            |_____________________|

      Figure 2: Flow chart of the expected state-of-the-art approach

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             _______________________
            |          1            |
            | Instructing the local |
            |     controller of     |
            |  data plane devices   |
            |_______________________|
                       |
                       |
                       |
             _______________________
            |          2            |
            | Local reconfiguration |
            |     upon failure      |
            |       detection       |
            |_______________________|
                       |
                       |
                       |
             _______________________
            |          3            |
            |                       |
            |     notification      |
            |                       |
            |_______________________|

    Figure 3: Flow chart of the approach exploiting YANG models in this
                                   draft

4.2.  Deploying Dynamic Probes for Programmable Network Telemetry

   In the past, network data analytics was considered a separate
   function from networks.  They consume raw data extracted from
   networks through piecemeal protocols and interfaces.  With the advent
   of user programmable data plane, we expect a paradigm shift that
   makes the data plane be an active component of the data telemetry and
   analytics solution.  The programmable in-network data preprocessing
   is efficient and flexible to offload some light-weight data
   processing through dynamic data plane programming or configuration.
   A universal network data analytics platform built on top of this
   enables a tight and agile network control and OAM feedback loop.  A
   proposed dynamic network telemetry system architecture is illustrated
   in Fig.4.

   An application translates its data requirements into a set of Dynamic
   Network Probes (DNP) targeting a subset of data plane devices.  After
   the probes are deployed, each probe conducts its corresponding in-
   network data preprocessing and feeds the preprocessed data to the

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   collector.  The collector finishes the data post-processing and
   presents the results to the data-requesting application.

                  +-------------------------------------+
                  |  network telemetry applications     |
                  +-------------------------------------+
                         ^                   |
                         |                   V
                         |         +--------------------+
                         |         | DNP compile/config |
                         |         +--------------------+
                         |                   |
                         |                   V
                  +---------------+ +--------------------+
                  |data collection| | Probe deployment   |
                  +---------------+ +--------------------+
                      ^   ^   ^            |   |   |
                      |   |   |            V   V   V
                  +--------------------------------------+
                  |  network data plane devices          |
                  | (in-network data preprocessing)      |
                  +--------------------------------------+

       Figure 4: Deploy dynamic network probes using YANG FSM models

   Many DNPs can be modeled as FSM which are configured to capture
   specific events.  Here FSMs essentially preprocess the raw stream
   data and only report the necessary data to subscribing applications.

   For example, a congestion control application needs to monitor the
   router buffer occupancy.  Instead of polling the buffer depth
   periodically, it is only interested in the real-time events when the
   buffer depth crosses a low and a high threshold.  We can install a
   probe to achieve this data plane function and the probe can be
   modeled as a three-state FSM.  Each state represents a buffer region:
   below the low threshold, above the high threshold, and in between the
   two thresholds.  A possible state transition is checked against the
   buffer depth for each incoming and outgoing packet.  Whenever a state
   transition happens, an event is generated and reported to the
   application.  This approach significantly reduces the amount of data
   sent to the application and also allows a timely event notification.

   For another example, an application would like to monitor the delay
   experienced by a flow.  The packet delay on its forwarding path can
   be acquired by using iOAM [I-D.brockners-inband-oam-requirements].
   However, the application only needs to know that N consecutive flow
   packets experience a delay longer than T.  Instead of forwarding the

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   raw delay data to the application, a probe can be deployed to detect
   the event.  Similarly, the probe can be modeled as an FSM.

4.3.  IP Performance Measurements on multipoint-to-multipoint large
      Networks

   Networks offer rich sets of network performance measurement data, but
   traditional approaches run into limitations.  One reason for this is
   the fact that in many cases, the bottleneck is the generation and
   export of the data and the amount of data that can be reasonably
   collected from the network runs into bandwidth and processing
   constraints in the network itself.  In addition, management tasks
   related to determining and configuring which data to generate lead to
   significant deployment challenges.

   In order to address these issues, an SDN controller application
   orchestrates network performance measurements tasks across the
   network to allow an optimized monitoring.  In fact the IP Performance
   Measurement SDN Controller Application in Figure 5 can calibrate how
   deep can be obtained monitoring data from the network by configuring
   measurement points roughly or meticulously.  This can be established
   by using the feedback mechanism reported in Figure 5.

   For instance, the SDN Controller can configure initially an end to
   end monitoring between ingress points and egress points of the
   network.  If the network does not experiment issues, this approximate
   monitoring is good enough and is very cheap in terms of network
   resources.  But, in case of problems, the SDN Controller becomes
   aware of the issues from this approximate monitoring and, in order to
   localize the portion of the network that has issues, configures the
   measurement points more exhaustively.  So a new detailed monitoring
   is performed.  After the detection and resolution of the problem the
   initial approximate monitoring can be used again.  This idea is
   general and can be applied to different performance measurements
   techniques both active and passive (and hybrid).

                   +--------------------------------------+
                   |      IP Performance Measurement      |
                   |      SDN Controller Application      |
                   +--------------------------------------+
                       ^   ^   ^            |   |   |
                       |   |   |            v   v   v
                   +--------------------------------------+
                   |          Multipoint Network          |
                   +--------------------------------------+

      Figure 5: Feedback mechanism on multipoint-to-multipoint large
                                 Networks

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   One of the most efficient methodology to perform packet, loss delay
   and jitter measurements both in an IP and Overlay Networks is the
   Alternate Marking method, as presented in [I-D.ietf-ippm-alt-mark]
   and [I-D.fioccola-ippm-multipoint-alt-mark].

   This technique can be applied to point-to-point flows but also to
   multipoint.to-multipoint flows (see [I-D.ietf-ippm-alt-mark] and
   [I-D.fioccola-ippm-multipoint-alt-mark]).  The Alternate Marking
   method creates batches of packets by alternating the value of 1 or 2
   bits of the packet header.  These batches of packets are
   unambiguously recognized over the network and the comparison of
   packet counters permits the packet loss calculation.  The same idea
   can be applied for delay measurement by selecting special packets
   with a marking bit dedicated for delay measurements.  This method
   needs two counters each marking period for each flow under monitor.
   For this reason by considering n measurement points and n monitored
   flows, the order of magnitude of the packet counters for each time
   interval is n*n*2 (1 per color).

   Multipoint Alternate Marking, described in
   [I-D.fioccola-ippm-multipoint-alt-mark], aims to reduce this value
   and makes the performance monitoring more flexible in case a detailed
   analysis is not needed.

   It is possible to monitor a Multipoint Network without examining in
   depth by using the Network Clustering (subnetworks that are portions
   of the entire network that preserve the same property of the entire
   network).  So in case there is packet loss or the delay is too high
   the filtering criteria could be specified more in order to perform a
   per flow detailed analysis, as described in [I-D.ietf-ippm-alt-mark].

   An application of the multipoint performance monitoring can be done
   by using FSM (each state is a composition of clusters) and feedback
   mechanism where the SDN Controller is the brain of the network and
   can manage flow control to the switches and routers and, in the same
   way, can calibrate the performance measurements depending on the
   necessity.

5.  YANG for finite state machine (FSM)

   This model defines a list of states and transitions to describe a
   generic finite state machine (FSM).  The related code and tree are
   shown in the Appendix.

 <current-state>: it defines the current state of the FSM.
 <states>: this element defines the FSM as follows.
           <state>: this list defines all the FSM states.
                  <id>: this leaf attribute of <state> defines the

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                  identifier of the state
                  <name>: this leaf attribute of <state> defines the
                  name of the state
                  <description>: this leaf is a "string" describing the
                  state
                  <transitions>: this attribute defines a list of
                  transitions to other states in the FSM.
                          <name>: this attribute defines the name of a
                          transition
                          <type>: this attribute defines the type of the
                          transition from a pool of possible transition
                          types predefined inside the YANG model.
                          Together with the <name> attribute, it
                          uniquely identifies the transition.
                          <description>: this optional attribute is a
                          "string" describing the transition
                          <filters>: this leaf is a list of input
                          parameters related to the transition. This
                          attribute enables to further express a
                          transition: as an example, if a transition can
                          be triggered by a parameter (e.g., a monitored
                          performance parameter) exceeding a threshold
                          (as in Sec. 5), an element of the list defines
                          this threshold. Thus, if the parameter is
                          outside the threshold, the transition is
                          taken, otherwise not.
                                <filter>: this leaf of <filters> defines
                                a filter parameter.
                                <filter-id>: this leaf of <filters>
                                define the identifier number associated
                                with the <filter> attribute.
                          <actions>: this attribute defines a list of
                          actions to take during the transition.
                                <action>: this attribute is the list of
                                actions
                                      <id>: this leaf of <action>
                                      defines the identifier number of
                                      an action.
                                      <type>: this leaf of <action>
                                      defines the type of an action.
                                      <simple>: this leaf defines
                                      (differently from <conditional>
                                      detailed below) an action that
                                      has to be directly executed.
                                            <execute>: this attribute
                                            recalls an RPC encapsulating
                                            the effective task (action)
                                            to be executed by the

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                                            hardware. If more actions
                                            (e.g., "A" and "B"), defined
                                            in the <action> list, have
                                            to be executed, these
                                            actions can be executed
                                            sequentially according to
                                            the <next-action> attribute
                                            detailed below. Thus, by
                                            referring to the tree of the
                                            Appendix, when an action
                                            ("A") is executed, the
                                            <next-action> attribute will
                                            bring to another action
                                            ("B"). If more actions have
                                            to be executed in parallel
                                            (e.g., "A" & "B"), not
                                            sequentially, an element of
                                            the <action> list should be
                                            defined to express an action
                                            (e.g., "A&B") consisting of
                                            more actions to be executed
                                            in parallel.
                                            <next-action>: this
                                            attribute defines the
                                            identification number of a
                                            next action that has to be
                                            taken.  The <next-action>
                                            can assume a NULL value.
                                      <conditional>: this leaf enables a
                                      check ("true" or "false") to be
                                      verified before executing the
                                      action. Based on the check, the
                                      proper attributes <execute> and
                                      <next-operation> are considered.
                                               <statement>: this leaf
                                               of <conditional> defines
                                               the condition to be
                                               verified before executing
                                               the action.
                                               <true>: this leaf of
                                               <conditional> defines a
                                               result of the check
                                               associated to
                                               <statement>. Proper
                                               <execute> and
                                               <next-operation>
                                               attributes are associated
                                               with this result of the

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                                               check.
                                               <false>: this leaf of
                                               <conditional> defines a
                                               result of the check
                                               associated to
                                               <statement>. Proper
                                               <execute> and
                                               <next-operation>
                                               attributes are associated
                                               with this result of the
                                               check.
                                 <next-state>: this attribute defines
                                 the next state of FSM when an action is
                                 executed.

6.  Implementation of the pre-programming resiliency schemes in EONs

   These presented model can be used to enable a centralized network
   controller, managed by a network operator, to instruct data plane
   hardware on its reconfiguration if some events, such as a failure or
   physical layer degradation, occur.  As an example, an optical signal
   impacted by a soft failure (i.e., a physical layer degradation
   inducing a pre forward error correction bit error rate increase -
   pre-FEC) can be maintained by adapting the FEC of the signal itself.
   This action to be taken and, more in general operations to be
   executed depending on critical events, can be (re-) programmed on the
   transponder by (re-) sending a NETCONF <edit-config> message to the
   device controller including a FSM defined by the YANG model.  Such a
   system has the main goal to speed up the reaction of the network to
   certain events/faults and to alleviate the workload of the
   centralized controller.  The speed up derives from the fact that the
   centralized controller is able to pre-compute and pre-configure on
   the network devices the actions to take when an event occurs taking
   into account a global view and knowledge of the network.  In this
   way, the device is already aware of the actions to be locally applied
   to reconfigure a connection, avoiding to inform the controller and to
   wait for the response indicating what to do.  Consequently, part of
   the workload is also removed from the centralized controller.  When
   the reaction is successfully completed in the data plane, the
   centralized controller can be notified about the faults and the taken
   action.  A flexible transponder supporting two FEC types, 7% and 20%,
   is considered.  A two-states FSM is also assumed.  The states have
   <name> attribute set to "Steady" and "Fec-Baud-Adapt", respectively.
   In the "Steady" state, the signal is in a healthy condition, adopting
   a 7% FEC, with a pre-FEC BER below an assigned threshold of 9 x 10-4.
   A transition from this state can be triggered by the event with
   <name>=BER_CHANGE and <filter-type>=9 x 10-4, thus expressing a
   change of the pre-FEC BER above the threshold.  In case the pre-FEC

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   BER exceeds 9 x 10-4 due to a soft failure, the state machine evolves
   to the "Fec-Baud-Adapt" state and an adaptation to a more robust FEC
   of 20% (executed by the attribute <execute>) is performed.  The
   system can return to the "Steady" state if the pre-FEC BER goes below
   another pre-defined threshold and the FEC is reconfigured to 7%.

7.  Appendix

   This appendix reports the YANG models code and the related tree.

7.1.  YANG model for FSM - Tree

   module: ietf-fsm
      +--rw current-state?   leafref
      +--rw states
         +--rw state [id]
            +--rw id             state-id-type
            +--rw description?   string
            +--rw transitions
               +--rw transition [name type]
                  +--rw name           string
                  +--rw type           transition-type
                  +--rw description?   string
                  +--rw filters
                  |  +--rw filter [filter-id]
                  |     +--rw filter-id    uint32
                  +--rw actions
                     +--rw action [id]
                        +--rw id             transition-id-type
                        +--rw type           enumeration
                        +--rw conditional
                        |  +--rw statement    string
                        |  +--rw true
                        |  |  +--rw execute
                        |  |  +--rw next-action?   transition-id-type
                        |  |  +--rw next-state?    leafref
                        |  +--rw false
                        |     +--rw execute
                        |     +--rw next-action?   transition-id-type
                        |     +--rw next-state?    leafref
                        +--rw simple
                           +--rw execute
                           +--rw next-action?   transition-id-type
                           +--rw next-state?    leafref

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7.2.  YANG model for FSM - Code

<CODE BEGINS> file "ietf-fsm@2016-03-15.yang"

 module ietf-fsm {

   namespace "http://sssup.it/fsm";

   prefix fsm;

   identity TRANSITION {

       description "Base for all types of event";

   }

   identity ON_CHANGE {

       base TRANSITION;

       description

         "The event when the database changes.";

   }

   // typedef statements

   typedef transition-type {

        description "it defines the type of transition (event)";

     type identityref {

       base TRANSITION;

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     }

   }

   typedef transition-id-type {
        description "it defines the id of the transition (event)";

     type uint32;

   }

   // grouping statements

   grouping action-block {

        description "it defines the action to perform when a transition occurs";

     leaf id {

description "it refers to the id of the transition";
       type transition-id-type;

     }

     leaf type {

description "it defines if the action has to be simply executed or if a conditional statement has to be checked before execution";

       type enumeration {

         enum "CONDITIONAL_OP" {
description "it defines the type CONDITIONAL OPERATION to check a statement before execution";
}

         enum "SIMPLE_OP" {
description "it defines the type SIMPLE OPERATION: i.e., an operation to be directly executed;
                }

       }

       mandatory true;

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     }

     grouping execution-top {

        description "it defines the execution attribute";

       anyxml execute {

         description "Represent the action to perform";

       }

       leaf next-action {

         type transition-id-type;

         description "the id of the next action to execute";

       }

     }

     container conditional {

        description "it defines the container CONDITIONAL";

       when "../type = 'CONDITIONAL_OP'";

       leaf statement {

         type string;

         mandatory true;

         description

           "The statement to be evaluated before execution.

           E.g. if a=b";

       }

       container true {

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description "it is referred to the result TRUE of a conditional statement ";

         uses execution-top;

       }

       container false {

description "it is referred to the result FALSE of a conditional statement ";

         uses execution-top;

       }

     }

     container simple {
description "Simple execution of an action without checking any condition";

       when "../type = 'SIMPLE_OP'";

       uses execution-top;

     }

   }

   grouping action-top {

description "it defines the grouping of action";

     list action {

description "it defines the list of actions";

       key "id";

       ordered-by user;

       uses action-block;

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     }

   }

   grouping on-change {

     description

       "Event occuring when a modification of one or more

        objects occurs";

     container filters {

       description

         "This container contains a list of configurable filters

          that can be applied to subscriptions.  This facilitates

          the reuse of complex filters once defined.";

       list filter {

         key "filter-id";

         description

           "A list of configurable filters that can be applied to

            subscriptions.";

         leaf filter-id {

           type uint32;

           description

             "An identifier to differentiate between filters.";

         }

       }

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     }

   }

   grouping transition-top {

description "it defines the grouping transition";

     leaf name {

description "it defines the transition name";

       type string;

       mandatory true;

     }

     leaf type {

description "it defines the transition type";

       type transition-type;

       mandatory true;

     }

     leaf description {

description "it describes the transition ";

       type string;

     }

     // list of all possible events

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     uses on-change {

       when "type = 'ON_CHANGE'";

     }

     container actions {

description "it defines the container action";

       uses action-top;

     }

   }

   grouping transitions-top {

description "it defines the grouping transition";

     container transitions {

description "it defines the container transitions";

       list transition {

description "it defines the list of transitions";

         key "name type";

         uses transition-top;

       }

     }

   }

   // data definition statements

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   uses transitions-top;

   // extension statements

   // feature statements

   // augment statements

   organization

     "Scuola Superiore Sant'Anna Network and Services Laboratory";

   contact

     " Editor: Matteo Dallaglio

               <mailto:m.dallaglio@sssup.it>

     ";

   description

     "This module contains a YANG definitions of a generic finite state
     machine.";

   revision 2016-03-15 {

     description "Initial Revision.";

     reference

       "RFC xxxx:";

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   }

   // identity statements

   // typedef statements

   typedef state-id-type {

description "it defines the id type of the states";

     type uint32;

   }

   // grouping statements

   grouping state-top {

description "it defines the grouping state";

     leaf id {

description "it defines the id of a transition";

       type state-id-type;

     }

     leaf description {

description "it describes a transition";

       type string;

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     }

     grouping next-state-top {

description "it defines the grouping for the next state";

       leaf next-state {

description "it defines the next state";

           type leafref {

description "it refers to its id";

             path "../../../../../../../../../states/state/id";

           }

           description "Id of the next state";

         }

     }

    uses transitions-top {

     augment "transitions/transition/actions/action/conditional/true" {

         uses next-state-top;

       }

     augment "transitions/transition/actions/action/conditional/false" {

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         uses next-state-top;

       }

     augment "transitions/transition/actions/action/simple" {

         //uses next-state-top;

         leaf next-state {

description "it defines the next state";

           type leafref {

 description "it refers to its id";
             path "../../../../../../../../states/state/id";

           }

           description "Id of the next state";

         }

       }

    }

   }

   grouping states-top {

description "it defines the grouping states";

     leaf current-state {

description "it defines the current state";

       type leafref {

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description "it refers to its id";
         path "../states/state/id";

       }

     }

     container states {
description "it defines the container states";

       list state {

   description "it defines the list of states";

         key "id";

         uses state-top;

       }

     }

   }

   // data definition statements

   uses states-top;

   // extension statements

   // feature statements

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   // augment statements.

   // rpc statements

 }//module fsm

<CODE ENDS>

7.3.  Example of values for the YANG model

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   FIELD NAME       |    YANG DATA TYPE   |        VALUE
   _________________|_____________________|________________________
   Current State    |       leafref       |  "an existing state id
                    |                     |       in the FSM"
                    |                     |
   State            |                     |
   id               |        uint32       |             1
   name             |        string       |          Steady
   description      |        string       |      "whatever string"
                    |                     |
   transition       |                     |
   name             |        string       |      "whatever string"
   type             |         enum        |         BER_CHANGE
   description      |        string       |      "whatever string"
                    |                     |
   filter           |                     |
   filter-id        |        uint32       |             2
   filter-type      |   anyxml or xpath   |         BER>0.0009
                    |                     |
   action           |                     |
   id               |        uint32       |             3
   type             |         enum        |          SIMPLE
   statement        |        string       |      "whatever string"
   execute          |        anyxml       | "this recalls an RPC
                    |                     |   where the FEC value
                    |                     |    is expressed"
   next-operation   |        uint32       |           NULL
   next-state       |       leafref       | "an existing state id
                    |                     |       in the FSM"

8.  Acknowledgements

   This work has been partially supported by the European Commission
   through the H2020 ORCHESTRA (Optical peRformanCe monitoring enabling
   dynamic networks using a Holistic cross-layEr, Self-configurable
   Truly flexible approach, grant agreement no: H2020-645360) project.
   The views expressed here are those of the authors only.  The European
   Commission is not liable for any use that may be made of the
   information in this document.

9.  Other Contributors

   Matteo Dallaglio (Scuola Superiore Sant'Anna), Andrea Di Giglio
   (Telecom Italia), Giacomo Bernini (Nextworks).

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10.  Security Considerations

   TBD

11.  IANA Considerations

   TBD

12.  References

12.1.  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>.

   [RFC6020]  Bjorklund, M., Ed., "YANG - A Data Modeling Language for
              the Network Configuration Protocol (NETCONF)", RFC 6020,
              DOI 10.17487/RFC6020, October 2010,
              <https://www.rfc-editor.org/info/rfc6020>.

   [RFC6241]  Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
              and A. Bierman, Ed., "Network Configuration Protocol
              (NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,
              <https://www.rfc-editor.org/info/rfc6241>.

   [RFC7491]  King, D. and A. Farrel, "A PCE-Based Architecture for
              Application-Based Network Operations", RFC 7491,
              DOI 10.17487/RFC7491, March 2015,
              <https://www.rfc-editor.org/info/rfc7491>.

12.2.  Informative References

   [I-D.brockners-inband-oam-requirements]
              Brockners, F., Bhandari, S., Dara, S., Pignataro, C.,
              Gredler, H., Leddy, J., Youell, S., Mozes, D., Mizrahi,
              T., <>, P., and r. remy@barefootnetworks.com,
              "Requirements for In-situ OAM", draft-brockners-inband-
              oam-requirements-03 (work in progress), March 2017.

   [I-D.fioccola-ippm-multipoint-alt-mark]
              Fioccola, G., Cociglio, M., Sapio, A., and R. Sisto,
              "Multipoint Alternate Marking method for passive and
              hybrid performance monitoring", draft-fioccola-ippm-
              multipoint-alt-mark-02 (work in progress), March 2018.

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   [I-D.ietf-i2rs-yang-network-topo]
              Clemm, A., Medved, J., Varga, R., Bahadur, N.,
              Ananthakrishnan, H., and X. Liu, "A Data Model for Network
              Topologies", draft-ietf-i2rs-yang-network-topo-20 (work in
              progress), December 2017.

   [I-D.ietf-ippm-alt-mark]
              Fioccola, G., Capello, A., Cociglio, M., Castaldelli, L.,
              Chen, M., Zheng, L., Mirsky, G., and T. Mizrahi,
              "Alternate Marking method for passive and hybrid
              performance monitoring", draft-ietf-ippm-alt-mark-14 (work
              in progress), December 2017.

   [I-D.song-opsawg-dnp4iq]
              Song, H. and J. Gong, "Requirements for Interactive Query
              with Dynamic Network Probes", draft-song-opsawg-dnp4iq-01
              (work in progress), June 2017.

   [I-D.vergara-ccamp-flexigrid-yang]
              Madrid, U., Perdices, D., Lopezalvarez, V., Dios, O.,
              King, D., Lee, Y., and G. Galimberti, "YANG data model for
              Flexi-Grid Optical Networks", draft-vergara-ccamp-
              flexigrid-yang-06 (work in progress), January 2018.

   [I-D.zhang-ccamp-l1-topo-yang]
              zhenghaomian@huawei.com, z., Fan, Z., Sharma, A., and X.
              Liu, "A YANG Data Model for Optical Transport Network
              Topology", draft-zhang-ccamp-l1-topo-yang-07 (work in
              progress), April 2017.

Authors' Addresses

   Nicola Sambo
   Scuola Superiore Sant'Anna
   Via Moruzzi 1
   Pisa  56124
   Italy

   Email: nicola.sambo@sssup.it

   Piero Castoldi
   Scuola Superiore Sant'Anna
   Via Moruzzi 1
   Pisa  56124
   Italy

   Email: piero.castoldi@sssup.it

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   Giuseppe Fioccola
   Telecom Italia
   Via Reiss Romoli, 274
   Torino  10148
   Italy

   Email: giuseppe.fioccola@telecomitalia.it

   Filippo Cugini
   CNIT
   Via Moruzzi 1
   Pisa  56124
   Italy

   Email: filippo.cugini@cnit.it

   Haoyu Song
   Huawei
   2330 Central Expressway
   Santa Clara, CA  95050
   USA

   Email: haoyu.song@huawei.com

   Tianran Zhou
   Huawei
   156 Beiqing Road
   Beijing  100095
   China

   Email: zhoutianran@huawei.com

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