TEAS WG Young Lee
Internet Draft Dhruv Dhody
Intended Status: standard Satish Karunanithi
Huawei
Ricard Vilalta
CTTC
Daniel King
Lancaster University
Daniele Ceccarelli
Ericsson
Expires: September 2017
March 13, 2017
YANG models for ACTN TE Performance Monitoring Telemetry and Network
Autonomics
draft-lee-teas-actn-pm-telemetry-autonomics-00
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Abstract
Abstraction and Control of TE Networks (ACTN) refers to the set of
virtual network operations needed to operate, control and manage
large-scale multi-domain, multi-layer and multi-vendor TE networks,
so as to facilitate network programmability, automation, efficient
resource sharing.
This document provides YANG data models that describe Key
Performance Indicator (KPI) telemetry and network autonomics for TE-
tunnels and ACTN VNs.
Table of Contents
1. Introduction...................................................3
2. Use-Cases......................................................3
3. Design of the Data Models......................................5
TE KPI Telemetry Model.........................................6
ACTN TE KPI Telemetry Model....................................7
4. Notification...................................................8
YANG Push Subscription Examples................................8
5. YANG Data Tree................................................10
6. Yang Data Model...............................................13
ietf-te-kpi-telemetry model...................................13
ietf-actn-te-kpi-telemetry model..............................21
7. Security Considerations.......................................26
8. IANA Considerations...........................................26
9. Acknowledgements..............................................26
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10. References...................................................26
Informative References........................................26
Normative References..........................................27
11. Contributors.................................................27
Authors' Addresses...............................................28
1. Introduction
Abstraction and Control of TE Networks (ACTN) describes a method for
operating a Traffic Engineered (TE) network (such as an MPLS-TE
network or a layer 1/0 transport network) to provide connectivity
and virtual network services for customers of the TE network [ACTN-
Frame]. The services provided can be optimized to meet the
requirements (such as traffic patterns, quality, and reliability) of
the applications hosted by the customers. Data models are a
representation of objects that can be configured or monitored within
a system. Within the IETF, YANG [RFC6020] is the language of choice
for documenting data models, and YANG models have been produced to
allow configuration or modeling of a variety of network devices,
protocol instances, and network services. YANG data models have been
classified in [Netmod-Yang-Model-Classification] and [Service-YANG].
[ACTN-VN-YANG] describes how customers or end to end orchestrators
can request and/or instantiate a generic virtual network service.
[ACTN-Applicability] describes a connection between IETF YANG model
classifications to ACTN interfaces. In particular, it describes the
customer service model can be mapped into the CMI (CNC-MDSC
Interface) of the ACTN architecture.
The YANG model on the ACTN CMI is known as customer service model in
[Service-YANG]. [PCEP-Service-Aware] describes key network
performance data to be considered for end-to-end path computation in
TE networks. Key performance indicator is a term that describes
critical performance data that may affect VN/TE service.
2. Use-Cases
[ACTN-PERF] describes use-cases relevant to this draft. It
introduces the dynamic creation, modification and optimization of
services based on the performance monitoring in the Abstraction and
Control of Transport Networks (ACTN) architecture. Figure 1 shows a
high-level workflows for dynamic service control based on traffic
monitoring.
Some of the key points from [ACTN-PERF] are as follows:
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. Network traffic monitoring is important to facilitate automatic
discovery of the imbalance of network traffic, and initiate the
network optimization, thus helping the network operator or the
virtual network service provider to use the network more
efficiently and save CAPEX/OPEX.
. Customer services have various SLA requirements, such as
service availability, latency, latency jitter, packet loss
rate, BER, etc. The transport network can satisfy service
availability and BER requirements by providing different
protection and restoration mechanisms. However, for other
performance parameters, there are no such mechanisms. In order
to provide high quality services according to customer SLA, one
possible solution is to measure the service SLA related
performance parameters, and dynamically provision and optimize
services based on the performance monitoring results.
. Performance monitoring in a large scale network could generate
a huge amount of performance information. Therefore, the
appropriate way to deliver the information in CMI and MPI
interfaces should be carefully considered.
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+-------------------------------------------+
| CNC +-----------------------------+ |
| | Dynamic Service Control APP | |
| +-----------------------------+ |
+-------------------------------------------+
1.Traffic| /|\4.Traffic | /|\
Monitor& | | Monitor | | 8.Traffic
Optimize | | Result 5.Service | | modify &
Policy | | modify& | | optimize
\|/ | optimize Req.\|/ | result
+------------------------------------------------+
| MDSC +-------------------------------+ |
| |Dynamic Service Control Agent | |
| +-------------------------------+ |
| +---------------+ +-------------------+ |
| | Flow Optimize | | vConnection Agent | |
| +---------------+ +-------------------+ |
+------------------------------------------------+
2. Path | /|\3.Traffic | |
Monitor | | Monitor | |7.Path
Request | | Result 6.Path | | modify &
| | modify& | | optimize
\|/ | optimize Req.\|/ | result
+-------------------------------------------------------+
| PNC +----------------------+ +----------------------+ |
| | Network Provisioning | |Abstract Topology Gen.| |
| +----------------------+ +----------------------+ |
| +------------------+ +--------------------+ |
| |Network Monitoring| |Physical Topology DB| |
| +------------------+ +--------------------+ |
+-------------------------------------------------------+
Figure 1 Workflows for dynamic service control based on traffic
monitoring
3. Design of the Data Models
The YANG models developed in this document describe two models:
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(i) TE KPI Telemetry Model which provides the TE-Tunnel level of
performance monitoring mechanism (See Section 2.1 for
details)
(ii) ACTN TE KPI Telemetry Model which provides the VN level of the
aggregated performance monitoring mechanism (See Section 2.2
for details)
The models include -
(i) Performance Telemetry details as measured during the last
interval, ex delay.
(ii) Scaling Intent based on with TE/VN could be scaled in/out.
[Editor's Note - Need to decide if scaling and telemetry can be in
the same model as per the current draft.]
TE KPI Telemetry Model
This module describes performance telemetry for TE-tunnel model. The
telemetry data is augmented to tunnel state. This module also
allows autonomic traffic engineering scaling intent configuration
mechanism on the TE-tunnel level. Various conditions can be set for
auto-scaling based on the telemetry data.
The TE KPI Telemetry Model augments the TE-Tunnel Model to enhance
TE performance monitoring capability. This monitoring capability
will facilitate proactive re-optimization and reconfiguration of TEs
based on the performance monitoring data collected via the TE KPI
Telemetry YANG model.
+------------+ +--------------+
| TE-Tunnel | | TE KPI |
| Model |<---------| Telemetry |
+------------+ augments | Model |
+--------------+
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ACTN TE KPI Telemetry Model
This module describes performance telemetry for ACTN VN model. The
telemetry data is augmented both at the VN Level as well as
individual VN member level. This module also allows autonomic
traffic engineering scaling intent configuration mechanism on the VN
level. Scale in/out criteria might be used for network autonomics in
order the controller to react to a certain set of variations in
monitored parameters.
Moreover, this module also provides mechanism to define aggregated
telemetry parameters as a grouping of underlying VN level telemetry
parameters. Grouping operation (such as maximum, mean) could be set
at the time of configuration. For example, if maximum grouping
operation is used for delay at the VN level, the VN telemetry data
is reported as the maximum {delay_vn_member_1, delay_vn_member_2, ..
delay_vn_member_N}. Thus, this telemetry abstraction mechanism
allows the grouping of a certain common set of telemetry values
under a grouping operation. This can be done at the VN-member level
to suggest how the E2E telemetry be inferred from the per domain
tunnel created and monitored by PNCs. One proposed example is the
following:
+------------------------------------------------------------+
| CNC |
| |
+------------------------------------------------------------+
1.CNC sets the | /|\ 2. MDSC gets VN Telemetry
grouping op, and | |
subscribes to the | | VN KPI TELEMETRY (VN Level)
VN level telemetry | | VN Bandwidth Utilization: Minimum
for delay and | | across VN members
bandwidth util | | VN Delay: Maximum across VN
\|/ | Members
+------------------------------------------------------------+
| MDSC |
| |
+------------------------------------------------------------+
The ACTN VN TE-Telemetry Model augments the basic ACTN VN model to
enhance VN monitoring capability. This monitoring capability will
facilitate proactive re-optimization and reconfiguration of VNs
based on the performance monitoring data collected via the ACTN VN
Telemetry YANG model.
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+----------+ +--------------+
| ACTN VN | augments | ACTN |
| Model |<---------| TE-Telemetry |
+----------+ | Model |
+--------------+
4. Notification
This model does not define specific notifications. To enable
notifications, the mechanism defined in [I-D.ietf-netconf-yang-push]
and [I-D.ietf-netconf-rfc5277bis] can be used. This mechanism
currently allows the user to:
. Subscribe notifications on a per client basis.
. Specify subtree filters or xpath filters so that only interested
contents will be sent.
. Specify either periodic or on-demand notifications.
YANG Push Subscription Examples
Below example shows the way for a client to subscribe for the
telemetry information for a particular tunnel (Tunnel1). The
telemetry parameter that the client is interested in is the utilized
bandwidth.
Tunnel1
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500
encode-xml
This example shows the way for a client to subscribe for the
telemetry information for all VNs. The telemetry parameter that the
client is interested in is packet-loss and utilized bandwidth.
500
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5. YANG Data Tree
A graphical representation of the complete data tree is presented
here. The meaning of the symbols in these diagrams is as follows
and as per [I-D.ietf-netmod-rfc6087bis]. Each node is printed as:
is one of:
+ for current
x for deprecated
o for obsolete
is one of:
rw for configuration data
ro for non-configuration data
-x for rpcs and actions
-n for notifications
is the name of the node
() means that the node is a choice node
:() means that the node is a case node
If the node is augmented into the tree from another module,
its name is printed as :.
is one of:
? for an optional leaf, choice, anydata or anyxml
! for a presence container
* for a leaf-list or list
[] for a list's keys
is the name of the type for leafs and leaf-lists
If the type is a leafref, the type is printed as "->
TARGET",
where TARGET is either the leafref path, with prefixed
removed if possible.
is the list of features this node depends on,
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printed within curly brackets and a question mark "{...}?
module: ietf-te-kpi-telemetry
augment /te:te/te:tunnels/te:tunnel/te:config:
+--rw te-scaling-intent
+--rw scale-in
| +--rw scale-in-operation-type?
| | scaling-criteria-operation
| +--rw threshold-time? uint32
| +--rw scale-in-condition* [performance-type]
| +--rw performance-type identityref
| +--rw performance-data? binary
+--rw scale-down
+--rw cooldown-time? uint32
+--rw scale-out-operation-type?
| scaling-criteria-operation
+--rw scale-out-condition* [performance-type]
+--rw performance-type identityref
+--rw performance-data? binary
augment /te:te/te:tunnels/te:tunnel/te:state:
+--ro te-telemetry
+--ro data
+--ro one-way-delay? uint32
+--ro two-way-delay? uint32
+--ro one-way-delay-min? uint32
+--ro one-way-delay-max? uint32
+--ro two-way-delay-min? uint32
+--ro two-way-delay-max? uint32
+--ro one-way-delay-variation? uint32
+--ro two-way-delay-variation? uint32
+--ro one-way-packet-loss? decimal64
+--ro two-way-packet-loss? decimal64
+--ro utilized-bandwidth? rt:bandwidth-ieee-float32
module: ietf-actn-te-kpi-telemetry
augment /actn-vn:actn/actn-vn:vn/actn-vn:vn-list:
+--rw vn-telemetry
| +--rw grouping-op
| +--rw delay-op? grouping-operation
| +--rw delay-variation-op? grouping-operation
| +--rw packet-loss-op? grouping-operation
| +--rw utilized-bandwidth-op? grouping-operation
+--rw vn-scaling-intent
+--rw scale-in
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| +--rw scale-in-operation-type?
| | scaling-criteria-operation
| +--rw threshold-time? uint32
| +--rw scale-in-condition* [performance-type]
| +--rw performance-type identityref
| +--rw performance-data? binary
+--rw scale-down
+--rw cooldown-time? uint32
+--rw scale-out-operation-type?
| scaling-criteria-operation
+--rw scale-out-condition* [performance-type]
+--rw performance-type identityref
+--rw performance-data? binary
augment /actn-vn:actn-state/actn-vn:vn/actn-vn:vn-list:
+--ro vn-telemetry
| +--ro grouping-op
| | +--ro delay-op? grouping-operation
| | +--ro delay-variation-op? grouping-operation
| | +--ro packet-loss-op? grouping-operation
| | +--ro utilized-bandwidth-op? grouping-operation
| +--ro data
| +--ro one-way-delay? uint32
| +--ro two-way-delay? uint32
| +--ro one-way-delay-min? uint32
| +--ro one-way-delay-max? uint32
| +--ro two-way-delay-min? uint32
| +--ro two-way-delay-max? uint32
| +--ro one-way-delay-variation? uint32
| +--ro two-way-delay-variation? uint32
| +--ro one-way-packet-loss? decimal64
| +--ro two-way-packet-loss? decimal64
| +--ro utilized-bandwidth? rt:bandwidth-ieee-float32
+--ro vn-scaling-intent
+--ro scale-in
| +--ro scale-in-operation-type?
| | scaling-criteria-operation
| +--ro threshold-time? uint32
| +--ro scale-in-condition* [performance-type]
| +--ro performance-type identityref
| +--ro performance-data? binary
+--ro scale-down
+--ro cooldown-time? uint32
+--ro scale-out-operation-type?
| scaling-criteria-operation
+--ro scale-out-condition* [performance-type]
+--ro performance-type identityref
+--ro performance-data? binary
augment /actn-vn:actn/actn-vn:vn/actn-vn:vn-list/actn-vn:vn-member-list:
+--rw vn-telemetry
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+--rw grouping-op
+--rw delay-op? grouping-operation
+--rw delay-variation-op? grouping-operation
+--rw packet-loss-op? grouping-operation
+--rw utilized-bandwidth-op? grouping-operation
augment /actn-vn:actn-state/actn-vn:vn/actn-vn:vn-list/actn-vn:vn-member-list:
+--ro vn-telemetry
+--ro grouping-op
| +--ro delay-op? grouping-operation
| +--ro delay-variation-op? grouping-operation
| +--ro packet-loss-op? grouping-operation
| +--ro utilized-bandwidth-op? grouping-operation
+--ro data
+--ro one-way-delay? uint32
+--ro two-way-delay? uint32
+--ro one-way-delay-min? uint32
+--ro one-way-delay-max? uint32
+--ro two-way-delay-min? uint32
+--ro two-way-delay-max? uint32
+--ro one-way-delay-variation? uint32
+--ro two-way-delay-variation? uint32
+--ro one-way-packet-loss? decimal64
+--ro two-way-packet-loss? decimal64
+--ro utilized-bandwidth? rt:bandwidth-ieee-float32
6. Yang Data Model
ietf-te-kpi-telemetry model
The YANG code is as follows:
file "ietf-te-kpi-telemetry@2017-03-13.yang"
module ietf-te-kpi-telemetry {
namespace "urn:ietf:params:xml:ns:yang:ietf-te-kpi-telemetry";
prefix "te-tel";
import ietf-te {
prefix "te";
}
import ietf-routing-types {
prefix "rt";
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}
organization
"IETF Traffic Engineering Architecture and Signaling (TEAS)
Working Group";
contact
"Editor: Young Lee
Editor: Dhruv Dhody
Editor: Ricard Vilalta
Editor: Satish Karunanithi ";
description
"This module describes telemetry for teas tunnel model";
revision 2017-03-13 {
description
"Initial revision. This YANG file defines
the reusable base types for TE telemetry.";
reference
"Derived from earlier versions of base YANG files";
}
/*
* Identities
*/
identity telemetry-param-type {
description
"Base identity for telemetry param types";
}
identity one-way-delay {
base telemetry-param-type;
description
"To specify average Delay in one (forward) direction";
}
identity two-way-delay {
base telemetry-param-type;
description
"To specify average Delay in both (forward and reverse)
directions";
}
identity one-way-delay-variation {
base telemetry-param-type;
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description
"To specify average Delay Variation in one (forward)
direction";
}
identity two-way-delay-variation {
base telemetry-param-type;
description
"To specify average Delay Variation in both (forward
and reverse) directions";
}
identity one-way-packet-loss {
base telemetry-param-type;
description
"To specify packet loss in one (forward) direction.";
}
identity two-way-packet-loss {
base telemetry-param-type;
description
"To specify packet loss in in both (forward and reverse)
directions";
}
identity utilized-bandwidth {
base telemetry-param-type;
description
"To specify utilized bandwidth over the specified source
and destination.";
}
/*
* Enums
*/
typedef scaling-criteria-operation {
type enumeration {
enum AND {
description
"AND operation";
}
enum OR {
description
"OR operation";
}
}
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description
"Operations to analize list of scaling criterias";
}
/*
* Groupings
*/
grouping telemetry-delay {
description
"Base telemetry delay parameters";
leaf one-way-delay {
type uint32;
units "microseconds";
description
"To specify average Delay in one (forward) direction
during the measurement interval";
}
leaf two-way-delay {
type uint32;
units "microseconds";
description
"To specify average Delay in both (forward and reverse)
directions during the measurement interval";
}
leaf one-way-delay-min {
type uint32;
units "microseconds";
description
"To specify minimum Delay in one (forward) direction
during the measurement interval";
}
leaf one-way-delay-max {
type uint32;
units "microseconds";
description
"To specify maximum Delay in one (forward) direction
during the measurement interval";
}
leaf two-way-delay-min {
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type uint32;
units "microseconds";
description
"To specify minimum Delay in both (forward and reverse)
directions during the measurement interval";
}
leaf two-way-delay-max {
type uint32;
units "microseconds";
description
"To specify maximum Delay in both (forward and reverse)
directions during the measurement interval";
}
}
grouping telemetry-delay-variance {
description
"Base telemetry delay variance parameters";
leaf one-way-delay-variation {
type uint32;
units "microseconds";
description
"To specify average Delay Variation in one (forward)
direction during the measurement interval";
}
leaf two-way-delay-variation {
type uint32;
units "microseconds";
description
"To specify average Delay Variation in both
(forward and reverse) directions during the
measurement interval";
}
}
grouping telemetry-packet-loss {
description
"Base telemetry packet loss parameters";
leaf one-way-packet-loss {
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type decimal64 {
fraction-digits 4;
range "0.0000..100.0000";
}
units "percent";
description
"To specify packet loss in one (forward) direction.";
}
leaf two-way-packet-loss {
type decimal64 {
fraction-digits 4;
range "0.0000..100.0000";
}
units "percent";
description
"To specify packet loss in in both (forward and reverse)
directions";
}
}
grouping telemetry-bandwidth {
description
"Base telemetry bandwidth parameters";
leaf utilized-bandwidth {
type rt:bandwidth-ieee-float32;
description
"To specify utilized bandwidth over the specified source
and destination in bytes per seconds.";
reference
"RFC 3471";
}
}
grouping scaling-criteria {
description
"Grouping for scaling criteria";
leaf performance-type {
type identityref {
base telemetry-param-type;
}
description
"Reference to the tunnel level telemetry type";
}
leaf performance-data {
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type binary;
description
"The encoding and meaning of this field is
based on the performance-type";
}
}
grouping scaling-intent {
description
"Basic scaling intent";
container scale-in {
description
"Basic scaling-in intent";
leaf scale-in-operation-type {
type scaling-criteria-operation;
default AND;
description
"Operation to be applied to check between
scaling criterias to check if the scale in
threshold condition has been met.
Defaults to AND";
}
leaf threshold-time {
type uint32;
units "seconds";
description
"The duration for which the criteria must
hold true";
}
list scale-in-condition {
key "performance-type";
description
"Scaling conditions";
uses scaling-criteria;
}
}
container scale-down {
description
"Basic scaling-out intent";
leaf cooldown-time {
type uint32;
units "seconds";
description
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"The duration after a scaling-in/scaling-out action
has been triggered, for which there will be no
further operation";
}
leaf scale-out-operation-type {
type scaling-criteria-operation;
default OR;
description
"Operation to be applied to check between
scaling criterias to check if the scale out
threshold condition has been met.
Defauls to OR";
}
list scale-out-condition {
key "performance-type";
description
"Scaling conditions";
uses scaling-criteria;
}
}
}
grouping telemetry-param {
description
"Base telemetry parameters";
container data {
description
"The telemetry data";
uses telemetry-delay;
uses telemetry-delay-variance;
uses telemetry-packet-loss;
uses telemetry-bandwidth;
}
}
/*
* Augments
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*/
augment "/te:te/te:tunnels/te:tunnel/te:config" {
description
"Augmentation parameters for config scaling-criteria
TE tunnel topologies. Scale in/out criteria might be
used for network autonomics in order the controller
to react to a certain set of monitored params.";
container te-scaling-intent {
description
"scaling intent";
uses scaling-intent;
}
}
augment "/te:te/te:tunnels/te:tunnel/te:state" {
description
"Augmentation parameters for state TE tunnel
topologies.";
container te-telemetry {
description
"telemetry params";
uses telemetry-param;
}
}
}//module
ietf-actn-te-kpi-telemetry model
The YANG code is as follows:
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file "ietf-actn-te-kpi-telemetry@2017-03-13.yang"
module ietf-actn-te-kpi-telemetry {
namespace
"urn:ietf:params:xml:ns:yang:ietf-actn-te-kpi-telemetry";
prefix "actn-tel";
import ietf-actn-vn {
prefix "actn-vn";
}
import ietf-te-kpi-telemetry {
prefix "te-kpi";
}
organization
"IETF Traffic Engineering Architecture and Signaling (TEAS)
Working Group";
contact
"Editor: Young Lee
Editor: Dhruv Dhody
Editor: Ricard Vilalta
Editor: Satish Karunanithi ";
description
"This module describes telemetry for actn vn model";
revision 2017-03-13 {
description
"Initial revision. This YANG file defines
the ACTN VN telemetry.";
reference
"Derived from earlier versions of base YANG files";
}
/*
* Typedefs
*/
typedef grouping-operation {
type enumeration {
enum MINIMUM {
description
"Select the minimum param";
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}
enum MAXIMUM {
description
"Select the maximum param";
}
enum MEAN {
description
"Select the MEAN of the params";
}
enum STD_DEV {
description
"Select the standard deviation of the
monitored params";
}
enum SUM {
description
"Select the sum of the monitored params";
reference
"RFC 7823";
}
enum LOSS_PERCENT {
description
"Select the packet loss percentage
calulation";
reference
"RFC 7823";
}
}
description
"Operations to analize list of monitored params";
}
/*
* Groupings
*/
grouping vn-telemetry-param {
description
"telemetry-parameter for VN";
uses te-kpi:telemetry-param;
}
grouping telemetry-grouping-op {
description
"Config how the VN telemetry should be applied";
container grouping-op {
description
"The grouping operations";
leaf delay-op {
type grouping-operation;
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default MAXIMUM;
description
"The operation that should be applied on the
VN-member telemetry to get the VN telemetry";
}
leaf delay-variation-op {
type grouping-operation;
default MAXIMUM;
description
"The operation that should be applied on the
VN-member telemetry to get the VN telemetry";
}
leaf packet-loss-op {
type grouping-operation;
default MAXIMUM;
description
"The operation that should be applied on the
VN-member telemetry to get the VN telemetry";
}
leaf utilized-bandwidth-op {
type grouping-operation;
default MAXIMUM;
description
"The operation that should be applied on the
VN-member telemetry to get the VN telemetry";
}
}
}
/*
* Augments
*/
augment "/actn-vn:actn/actn-vn:vn/actn-vn:vn-list" {
description
"Augmentation parameters for state TE VN topologies.";
container vn-telemetry {
description
"VN telemetry configurations";
uses telemetry-grouping-op;
}
container vn-scaling-intent {
description
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"scaling intent";
uses te-kpi:scaling-intent;
}
}
augment "/actn-vn:actn-state/actn-vn:vn/actn-vn:vn-list" {
description
"Augmentation parameters for state TE VN topologies.";
container vn-telemetry {
description
"VN telemetry params";
uses telemetry-grouping-op;
uses vn-telemetry-param;
}
container vn-scaling-intent {
description
"scaling intent";
uses te-kpi:scaling-intent;
}
}
/*
* VN-member augment
*/
augment "/actn-vn:actn/actn-vn:vn/actn-vn:vn-list/" +
"actn-vn:vn-member-list" {
description
"Augmentation parameters for state TE vn member
topologies.";
container vn-telemetry {
description
"VN Member config";
uses telemetry-grouping-op;
}
}
augment "/actn-vn:actn-state/actn-vn:vn/actn-vn:vn-list/" +
"actn-vn:vn-member-list" {
description
"Augmentation parameters for state TE vn member
topologies.";
container vn-telemetry {
description
"VN telemetry params";
uses telemetry-grouping-op;
uses vn-telemetry-param;
}
}
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}
7. Security Considerations
The configuration, state, and action data defined in this document
are designed to be accessed via a management protocol with a secure
transport layer, such as NETCONF [RFC6241]. The NETCONF access
control model [RFC6536] provides the means to restrict access for
particular NETCONF users to a preconfigured subset of all available
NETCONF protocol operations and content.
A number of configuration data nodes defined in this document are
writable/deletable (i.e., "config true") These data nodes may be
considered sensitive or vulnerable in some network environments.
8. IANA Considerations
TDB
9. Acknowledgements
10. References
Informative References
[RFC4110] R. Callon and M. Suzuki, "A Framework for Layer 3
Provider-Provisioned Virtual Private Networks (PPVPNs)",
RFC 4110, July 2005.
[RFC6020] M. Bjorklund, Ed., "YANG - A Data Modeling Language for
the Network Configuration Protocol (NETCONF)", RFC 6020,
October 2010.
[Service-YANG] Q. Wu, W. Liu and A. Farrel, "Service Models
Explained", draft-wu-opsawg-service-model-explained, work
in progress.
[Netmod-Yang-Model-Classification] D. Bogdanovic, B. Claise, and C.
Moberg, "YANG Module Classification", draft-ietf-netmod-
yang-model-classification, work in progress.
[Netconf] Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
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and A. Bierman, Ed., "Network Configuration Protocol
(NETCONF)", RFC 6241.
[Restconf] A. Bierman, M. Bjorklund, and K. Watsen, "RESTCONF
Protocol", draft-ietf-netconf-restconf, work in progress.
Normative References
[ACTN-Frame] D. Cecarelli and Y. Lee, "Framework for Abstraction and
Control of Traffic Engineered Networks", draft-ietf-teas-
actn-framework, work in progress.
[TE-Topology] X. Liu, et al., "YANG Data Model for TE Topologies",
draft-ietf-teas-yang-te-topo, work in progress.
[TE-Tunnel] T. Saad (Editor), "A YANG Data Model for Traffic
Engineering Tunnels and Interfaces", draft-ietf-teas-yang-
te, work in progress.
[ACTN-VN-YANG] Y. Lee (Editor), "A Yang Data Model for ACTN VN
Operation", draft-lee-teas-actn-vn-yang, work in progress.
[L3SM-YANG] S. Litkowski, L.Tomotaki, and K. Ogaki, "YANG Data Model
for L3VPN service delivery", draft-ietf-l3sm-l3vpn-
service-model, work in progress.
[PCEP-Service-Aware] D. Dhody, et al., "Extensions to the Path
Computation Element Communication Protocol (PCEP) to
compute service aware Label Switched Path (LSP)", draft-
ietf-pce-pcep-service-aware, work in progress.
[ACTN-PERF] Y. XU, et al., "Use Cases and Requirements of Dynamic
Service Control based on Performance Monitoring in ACTN
Architecture", draft-xu-actn-perf-dynamic-service-control-
03, work in progress.
11. Contributors
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Authors' Addresses
Young Lee
Huawei Technologies
5340 Legacy Drive Suite 173
Plano, TX 75024, USA
Email: leeyoung@huawei.com
Dhruv Dhody
Huawei Technology
Leela Palace
Bangalore, Karnataka 560008
India
Email: dhruv.dhody@huawei.com
Satish Karunanithi
Huawei Technology
Leela Palace
Bangalore, Karnataka 560008
India
Email: satish.karunanithi@gmail.com
Ricard Vilalta
Centre Tecnologic de Telecomunicacions de Catalunya (CTTC/CERCA)
Av. Carl Friedrich Gauss 7
08860 - Castelldefels
Barcelona (Spain)
Email: ricard.vilalta@cttc.es
Daniel King
Lancaster University
Email: d.king@lancaster.ac.uk
Daniele Ceccarelli
Ericsson
Torshamnsgatan,48
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Stockholm, Sweden
Email: daniele.ceccarelli@ericsson.com
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