Internet DRAFT - draft-km-detnet-for-ocn
draft-km-detnet-for-ocn
Detnet Group K. Makhijani
Internet-Draft Futurewei
Intended status: Informational T. Faisal
Expires: 14 September 2023 King's College London
R. Li
C. Westphal
Futurewei
13 March 2023
Using Deterministic Networks for Industry Operations and Control
draft-km-detnet-for-ocn-00
Abstract
Remote industrial process control & operations improve automation,
resource efficiency, safety and better overall control from the
software-defined application logic. So far, industrial/process
automation connectivity is mostly localized. In order to use cloud-
based connectivity, not only deterministic networks are needed but an
interface between the endpoints and the DetNet is required to be
clearly described. This document describes an interface to
deterministic networks from the view of end-points to support process
control and operations.
Status of This Memo
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Copyright Notice
Copyright (c) 2023 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
2.1. Acronyms . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Background on Industrial Control Systems . . . . . . . . . . 5
3.1. Connected Controllers, Sensors and Actuators . . . . . . 6
3.2. Traffic Patterns . . . . . . . . . . . . . . . . . . . . 7
3.2.1. Control Loops . . . . . . . . . . . . . . . . . . . . 7
3.2.2. Periodicity . . . . . . . . . . . . . . . . . . . . . 8
3.2.3. Ordering . . . . . . . . . . . . . . . . . . . . . . 8
3.2.4. Urgency . . . . . . . . . . . . . . . . . . . . . . . 8
3.3. Communication Patterns . . . . . . . . . . . . . . . . . 9
4. Gap Analysis . . . . . . . . . . . . . . . . . . . . . . . . 9
4.1. Deterministic Networks Relevance . . . . . . . . . . . . 9
4.2. DetNet related Considerations and Dependencies . . . . . 10
4.2.1. Operator vs Application view . . . . . . . . . . . . 11
4.2.2. Flow reservation and classification . . . . . . . . . 11
4.2.3. Split Traffic flows . . . . . . . . . . . . . . . . . 12
4.2.4. Provisioning for variety of Traffic flows . . . . . . 12
4.2.5. Security . . . . . . . . . . . . . . . . . . . . . . 13
4.3. Summary of Gaps . . . . . . . . . . . . . . . . . . . . . 13
5. DetNet Potential Approach . . . . . . . . . . . . . . . . . . 14
5.1. Application association to Forwarding sub-layer . . . . . 14
5.2. Encapsulation . . . . . . . . . . . . . . . . . . . . . . 14
5.3. Operation and Control Network Option (OCNO) . . . . . . . 15
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 16
7. Security Considerations . . . . . . . . . . . . . . . . . . . 16
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 16
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 16
9.1. Normative References . . . . . . . . . . . . . . . . . . 16
9.2. Informative References . . . . . . . . . . . . . . . . . 17
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 18
1. Introduction
Traditional industrial networks are designed to support process
automation within a production plant or a manufacturing floor.
Therefore, the network was typically a campus-area, local network and
it played an important but not a critical role. Now, as equipment
control and monitoring become remotely supported from the cloud or
the edge, network technologies such as TSN, and DetNet in particular,
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are gaining relevance.
Process automation systems involve operating a piece of equipment
(such as actuating and/or sensing field-devices. The communication
between the controllers and field-devices exhibits a well-defined set
of behaviors and has specific characteristics: the delivery of a
control-command to a machine must be executed within the time-frame
specified by a controller or by an application to provide reliable
and secure operation. A low or zero tolerance to latency and packet
losses (among other things) is implied. In this document, these
special purpose networks are referred to as operation and control
networks (OCNs) [OCN-MODEL].
DetNets provide mechanisms for guaranteed packet delivery in-time,
for reliability, and for packet loss mitigation. Thus, the OCNs are
an application's view of a network and DetNet is one of the potential
underlying enabling technology.
The packet processing in DetNet is associated with a flow. A DetNet
service deals with aggregated flows for which a network service
provider would engineer and allocate resources. Thus, the networks
are provisioned for less dynamic (long-lived) scenarios. However,
OCN-type traffic patterns arise from the programmatic behavior of an
application. Hence they can be dynamic, sporadic and intermittent.
This leads to the issue of how applications can interact with the
DetNet-enabled networks.
This document outlines the opportunities to make DetNet more amenable
to OCN environments, by describing the interface between the OCN
application and DetNets i.e., using DetNet services for communication
between the controllers and the field-devices. This interface is
used by an application to express its network-specific requirements.
The document presents the perspective of an end-system that is a
'process-control & operation' type of cloud-hosted application.
Because most cloud-hosted applications would rely on IP, we consider
first these specific to IP-enabled DetNet data planes [DETNET-DP].
Hence the discussions will assume IP-base end-systems. For the other
type of end-systems, the field-devices, service level proxy functions
are assumed (as per section 4.1 in RFC8655).
The rest of the document presents a special case of DetNet referred
to as Operation and Control Networks (OCN). Section 3 provides a
background on the type of traffic for OCN applications. In the
context of interface between an application and DetNet, some of the
limitations in IP-enabled Detnets are covered in Section 4. The
document is intended to discuss possible approaches or potential
solution direction to support OCN traffic patterns over DetNet, as
covered in Section 5.
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2. Terminology
* Operational Technology (OT): Programmable systems or devices that
interact with the physical environment (or manage devices that
interact with the physical environment). These systems/devices
detect or cause a direct change through the monitoring and/or
control of devices, processes, and events. Examples include
industrial control systems, building management systems, fire
control systems, and physical access control mechanisms.
Source: [NIST-OT]
* Industry Automation: Mechanisms that enable machine-to-machine
communication by use of technologies that enable automatic
control and operation of industrial devices and processes
leading to minimizing human intervention.
* Control Loop: Control loops are part of process control systems
in which desired process response is provided as input to the
controller, which performs the corresponding action (using
actuators) and reads the output values. Since no error
correction is performed, these are called open control loops.
* Feedback Control Loop: A feedback loop is part of a system in
which some portion (or all) of the system's output is used as
input for future operations.
* Industrial Control Networks: Industrial control networks are the
interconnection of equipment used for the operation, control or
monitoring of machines in the industry environment. It
involves a different level of communication - between fieldbus
devices, digital controllers and software applications
* Human Machine Interface (HMI): An interface between the operator
and the machine. The communication interface relays I/O data
back and forth between an operator's terminal and HMI software
to control and monitor equipment.
2.1. Acronyms
* HMI: Human Machine Interface
* OCN: Operations and Control Networks
* PLC: Programmable Logic Control
* OT: Operational Technology
* OC: Operation and Control
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* OCN: Operation and Control Networks
3. Background on Industrial Control Systems
An industry control network interconnects devices used to operate,
control and monitor physical equipment in industrial environments.
Figure 1 below shows such systems' reference model and functional
components. Closest to the physical equipment are field devices
(actuators and sensors) that connect to the Programmable Logic
Controllers (PLCs) or other types of controllers using serial bus
technologies (and now Ethernet). Above those controllers are Human
Machine Interface (HMI) connecting different PLCs and performing
several controller functions along with exchanging data with the
applications.
A factory floor is divided into cell-sites. The PLCs or other types
of controllers are physically located close to the equipment in the
cell-sites. The collection of monitoring, status and sensing data is
first done on the site and then transmitted over secure channels to
the cloud applications.
+-+-+-+-+-+-+
^ | Data Apps |.... External business-logic
: +-+-+-+-+-+-+ : Network
: | :
v +-+-+-+-+-+-+ +-+-+-+-+--+
| vendor A | |vendor B | Interconnection of
| controller| |controller| controllers
^ +-+-+-+-+-+-+ +-+-+-+-+-+ (system integrators)
: | |
: +-+-+-+-+ +-+-++-+
: | Net X | | Net Y|
v | PLCs | | PLCs |--+ device-controllers
^ +-+-+-+-+ +-+-+--+ |
: | | |
: +-+-+ +-+-+ +-+-+
v | | | | | | Field devices
+-+-+ +-+-+ +-+-+
Figure 1: Functions in Industrial Control Networks
What is changing now is that cloud applications are integrating
process control functions to improve automation and to make real-time
decisions, programmatically. The equipment control and collection of
data generated by the sensors can be done directly over DetNet-
enabled wide-area networks as illustrated in Figure 2.
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+-+-+-+-+-+-+-+-+
| Data Apps | Integrated Apps with
| c1 | c2 | c3 | Remote process control
+-+-+-+-+-+-+-+-+
\ ,-----. /
+-[ Det- ]-+
[Network]
`-----'
+-+-+-| |-+-+-+-+
| | |
+-+-+ +-+-+ +-+-+
| | | | | | Field devices
+-+-+ +-+-+ +-+-+
Figure 2: Converged Cloud based Industrial Control Networks
One particular motivation is to provide the behavior of a serial bus
between the cloud and the actuators/sensors with the same assurance
of reliability and latency, albeit over wide-area networks (WAN).
This is evident from many Industry control applications, such as
factory automation [FACTORY], PLC virtualization [VIRT-PLC], power
grid operations [PTP-GRID], etc. that are now expected to operate in
the cloud by leveraging virtualization and shared infrastructure
wherever possible.
3.1. Connected Controllers, Sensors and Actuators
Control systems comprise Controllers, Sensors and Actuators. The
data traffic essentially carries instructions that cause machines or
equipment to move and do things within or at a specific time. The
connectivity exists in the following manner:
* A controller interfaces with the sensors and actuators. The
controller knows an application's performance parameters which are
expressed in terms of network specific requests or resources such
as tolerance to packet loss, latency limits, jitter variance,
bandwidth, and specification for safety. The controller knows all
the packet delivery constraints.
* An actuator receives specific commands from the controllers. The
DetNet should be able to enable control of actuating devices
remotely from the controller while meeting all the requirements
(or key performance indicators - KPIs) necessary for successful
command execution. The actuator participates in a closed control
loop as needed.
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* A sensor emit periodic data from the sensors. It may
intermittently provide asynchronous readings upon request from the
controller. Sensors may report urgent messages regarding
malfunctioning in certain equipment, cell-sites, or zones.
Almost all control systems have at least one controlling entity on
one end, and two other end points - the sensors and actuators. The
interface to sensors and actuators is through the controllers; i.e.,
applications do not directly interact with the field-devices.
Neither actuators nor sensors perform decision-making tasks. This
responsibility belongs to the controller.
3.2. Traffic Patterns
For either local or wide area, the process automation activities over
the network can generate a variety of traffic patterns between the
controllers and field-devices such as:
3.2.1. Control Loops
The equipment being operated upon is sensitive to when a command
request actually executes. An actuator upon receiving a command
(function code) will immediately perform the corresponding action.
It is the responsibility of network and controller to ensure that
behavior of the sensor and actuator follows the expectations of
applications.
For several such applications, the knowledge of a successful
operation is equally critical to advance to the next steps;
therefore, getting the response back in a specified time is required,
leading to a knowledge of timing. These types of bounded-time
request and response mechanisms are called control loops.
Unlike general purpose applications, commands cannot be batched, the
parameters of the command that will follow depends on the result of
the previous one. Each request in control loop takes up a minimal
payload size (function code, value, device or bus address) and will
often fit in a single short packet.
In Detnet-enabled network, it can be imagined as a small series of
packets with the same flow identifier, but with different latency
constraints.
It is required to support control loops where each request presents
its own latency constraints to the network and where commands are
small sized packets.
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3.2.2. Periodicity
Sensors emit data at regular intervals, but this information may not
always be time-constrained. Usually, controllers are programmed to
tolerate and record intermittent losses. Automation software can
make a more informed decision by monitoring a lot of sensor data.
Thus, the traffic volume generated by sensors is expected to high.
The periodicity of each sensor can also vary based on the equipment.
It is required that network capacity is planned appropriately for the
periodic traffic generated from the different sensors. The periodic
interval should also be preserved in the network because any
variations could provide false indications that the equipment is
misbehaving.
3.2.3. Ordering
In real-time process control communications, out of order message
processing will lead to costly failures of operations. Messages such
as request and reply, or a sequence of commands may be correlated
therefore, both time constraints and order must be preserved. The
traffic is generated when software triggers control-commands to
field-devices. This may not always map into asynchronous DetNet
flows if observation interval is not known.
The network should be capable of supporting sporadic on-demand short-
term flows. This does not imply instantaneous resource provisioning,
instead it would be more efficient if the provisioned resources could
be shared for such asynchronous traffic patterns.
Another consideration with ordering is that both actuators and
sensors are low-resource devices. They can not buffer multiple
packets and execute them in order while maintaining the latency
bounds of each command execution. This means the network must pace
packets that may arrive early.
3.2.4. Urgency
Besides latency constrained and periodic messages, sensors also
report failures as fault notifications, such as pressure valve
failure, abnormally high humidity, etc. These messages must be
delivered with utmost urgency and immediately.
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3.3. Communication Patterns
Control systems follow a specific communication discipline. The
field-devices (sensors and actuators) are always controlled, i.e.,
interact with the system through controllers in the following
manner:-
* Sensor to controller: data emitted at periodic interval providing
status/health of the environment or equipment. The traffic volume
for this communication is determined by the payload size of each
sensor data and the interval. These are a kind of synchronous
Detnet flows but with much higher time intervals; still the inter-
packet gap should be minimum.
* Controller to/from actuator: the commands/instructions to write or
read. Actuators generally do not initiate a command unless
requested by the controller. Actuators will often execute a
command, read the corresponding result, and send that in response
to the original write command. The traffic profile will be
balanced in both directions due to requests/ response behavior.
These are like asynchronous flows but without the observation
interval constraint.
4. Gap Analysis
Today, most of the operations and control solutions are split
approaches. This means that the controller is on-premises close to
the equipment, sensor data is also collected on-site and then
transmitted to the cloud for further processing.
To support delivering remote instructions to the machines over wide-
area networks using Deterministic Network data plane architecture
[DETNET-DP] and corresponding data plane DetNet over IP [DETNET-IP]
mechanisms apply as discussed in Section 4.1. Later in Section 4.2
additional asks from DetNet are covered.
4.1. Deterministic Networks Relevance
Note: This section's text and explanation on DetNet can be
removed.
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DetNet IP Relay Relay DetNet IP
End System Node Node End System
+----------+ +----------+
| Appl. |<------------ End-to-End Service ----------->| Appl. |
+----------+ ............ ........... +----------+
| Service |<-: Service :-- DetNet flow --: Service :->| Service |
+----------+ +----------+ +----------+ +----------+
|Forwarding| |Forwarding| |Forwarding| |Forwarding|
+--------.-+ +-.------.-+ +-.---.----+ +-------.--+
: Link : \ ,-----. / \ ,-----. /
+......+ +----[ Sub- ]----+ +-[ Sub- ]-+
[Network] [Network]
`-----' `-----'
|<--------------------- DetNet IP --------------------->|
Figure 3: A Simple DetNet-Enabled IP Network, Ref. RFC8939
Figure 3 is described in the DetNet IP dataplane [RFC8939] and
illustrates a DetNet-IP network. The DetNet-enabled end systems
originate traffic encapsulated with Detnet forwarding and service
sub-layers; otherwise some attached relay node will create the Detnet
sub-layers based on information received from the end system. The
forwarding sub-layer is responsible for resource allocation and
explicit path functions, whereas the service sublayer provides packet
replications, sequence numbering, and other functions. Within the
Detnet nodes, resources are allocated a priori for a flow.
The DetNet supports both asynchronous (by allocating resources for
the observation interval) and synchronous (with repeating schedules)
flow behaviors (Section 4.3.2 in [DETNET-DP]). The granularity of
DetNet services is at the flow level (6-tuple flow, including DSCP).
Realistically, leveraging DetNets for Operations and Control (OCN)
traffic patterns Section 3.2 can be challenging for the reasons
described next.
4.2. DetNet related Considerations and Dependencies
Per the Detnet architecture, a DetNet-aware node should express the
network requirements as part of forwarding sublayer or service-
sublayer. The [DETNET-IP] spec doesnot specify how sublayers are
mapped in 6-tuple flow.
In case of operations & control-application, a DetNet service
consumer will need to provide a service-level manifest to the DetNet
service provider (DN-SP) for each controller and field-device pair.
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The DN-SP is expected to allocate resources and return a mapping of a
DSCP (DetNEt Qos) for each pair. This could be become a scaling
problem as the number of controller-device pairs start to grow.
Given that only DSCP is available, field-device pair can pose issues
such as:
* How can application request the proper network-resource for each
command?
* How can an application receive periodic data from sensors?
* What are the ways to differentiate a less sensitive (periodic)
updates from urgent alarms.
* Or how to differentiate data received from a sensor or actuator
and process them accordingly.
These issues are described below in more detail.
4.2.1. Operator vs Application view
The DetNet data plane is designed with a network-operator-centric
approach. In order to use resources efficiently, there is an
emphasis on aggregation of several flows together. The operators in
Industrial control networks are not necessarily network experts; they
will face complexities in presenting a request to the DetNet
forwarding engine. Especially, an application is written to control
a set of field-devices and monitor a different set of sensors and
will need to learn the mappings for each controller-field-device
(ctrl-flddev) pair to the applicable DetNet flows.
As the number of ctrl-flddev pairs grow, their variable traffic
profiles can become hard to manage.
An OCN application is unaware of how DetNet services are provisioned.
A common UNI between the applications and DetNet-enabled network
needs to be added to the current framework to better map the
expectations better.
4.2.2. Flow reservation and classification
Inside the DetNet, flow identification is done using IP header and
DSCP information. These flow identifiers are then used by DetNet
nodes to provide the corresponding traffic treatment. Accordingly,
resources are provisioned over longer timescales, i.e., the model
works for relatively predictable scenarios. The problem is that the
control loops in Section 3.2.1 may be short messages so that one
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command is sent per packet, expecting a response from the actuator in
another return packet. The transmission of the next set of commands
is driven programmably by the applications. This is how the
softwarization of industrial processes is happening now.
Perhaps, it can be stated that the provisioning resources for flows
does not necessarily guarantee that the Detnet-specific resource
contention at the instant will not occur.
Moreover, for any cloud-based solution, controller may as well send
commands to the devices from different locations (different IP
addresses), thus the scale of provisioned flows can grow very fast.
To utilize Detnet-specific resources, it is needed to embed specific
information in addition to DSCP, so that dynamic traffic patterns can
be scheduled deterministically.
4.2.3. Split Traffic flows
One of the most constrained design elements in today's industrial
control systems is that data from the sensors is collected on-site
and often aggregated before transporting to the cloud. Historical
reasons for this approach do not apply anymore. Due to growth in
sensor data, it now requires a much larger on-site storage
infrastructure which is expensive. Applications also expect real-
time streaming telemetry data. Although latency constraints are not
as strict as for control loops, sensor data need to preserve
periodicity (Section 3.2.2), and also requires DetNet service
support.
Leveraging DetNet could eliminate split traffic flows by collecting
the sensor data by the applications. This also allows controllers to
be run and operated from the cloud platforms where much more powerful
compute capabilities and available.
4.2.4. Provisioning for variety of Traffic flows
Different operational scenarios have different constraints; even
commands within the same application will have different time
requirements.
* Different types of latency bounds will be required between a
controller and an actuator pair based on the type of end-equipment
and precision requirements. Out-of-order message processing may
lead to failures and shutdown of operations. Messages may also be
correlated. Therefore, time constraints may be applied on a
single message or on a group of messages.
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* Similarly, each sensor-controller pair may come with its own
interval requirement. Sensors emit data at regular interval but
this type of information may not always be time-constrained. The
gaps between the period can provide an indication to the
controller about communication or other problems.
* Additionally, some faults and alarm messages are urgent reports
and must be marked and transmitted accordingly.
It is not clear if all these variations can be predictably resolved
without any additional information offered to the DetNet forwarding
plane. For example, if two independent OCN flowlets (that is,
ordered group of packets that are related at process control logic)
with variable bounded latency are classified to the same DetNet flow,
they will receive the same treatment, regardless if one has the
shorter latency than the other and may end up behind a flowlet with
longer latency value. On the other hand, if an OCN flowlet have
packets with different latency values, they could end up in different
DetNet flow and may not reach destination in a specific order.
4.2.5. Security
Industry control networks also have split security boundaries. They
have been designed to be air-gapped or secure by separation. Current
systems have strict admission control, ingress and egress policies.
From network layer security perspective, how DetNet-enabled network
deals with security falls in the [RFC9055], the end-systems expect
those mechanisms in place. In particular if additional information
is distributed for datapath decisions, integrity protection as per
Section 7.2 of [RFC9055].
The border gateways and firewalls will be more prone to errors
related to provisioning churns if the system is dynamic or
continuously changing.
The transport layer deals with the end-to-end encryption. It should
evolve to incorporate additional IoT-friendly(lightweight) protocols
such as COAP, MQTT and their encryption mechanisms.
4.3. Summary of Gaps
* Application view (Section 4.2.1: An OCN application is unaware of
how DetNet services are provisioned. A common UNI between the
applications and DetNet-enabled network needs to be added to the
current framework to better map the expectations better.
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* Security (Section 4.2.5): of process control related metadata to
be used by network must be secured.
* Traffic behavior (Section 4.2.4 and Section 4.2.2): Within the
same DetNet flow, classified via 6-tuple, additional information/
metadata must be supported so that dynamic traffic patterns can be
scheduled deterministically.
* Split traffic (Section 4.2.3): Leveraging DetNet should eliminate
split traffic flows by direct collection of sensor data by the
applications. This also allows controllers to be run and operated
from the cloud platforms where much more powerful compute
capabilities are available.
5. DetNet Potential Approach
Remote process automation presents different types of traffic
profiles and to deal with them within the DetNet framework, we
discuss few possibilities.
The DetNet UNI will enable applications to convey specific
requirements to DetNet-aware Network. Note, that it is just an
interface and blind to the internal implementation of such networks.
The DetNet architecture does not describe how DetNet-aware node can
design DetNet sub-layers. But even from the view of an end-system
the separation between forwarding and service sublayer functions
should be maintained. This means, the DSCP should not be overloaded
and DetNet-IP forwarding layer should be extended.
5.1. Application association to Forwarding sub-layer
Applications should convey specific resource requirements to the
DetNets they connect to. There are two potential options: (a) The
DetNet Relay-node performs translation and binding to one of the
DetNet services in the DetNet; or (b) or carry the application
defined data over DetNet as is and enable processing on transit
nodes.
5.2. Encapsulation
Note that the applications in this context are in the cloud, IP is
expected for the end-stations (MPLS DetNet will not apply). It is
also reasonable to assume that the data plane is IPv6 and extension
headers are used for support in DetNet.
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The end-system network requirement is expressed as 'Flowlet or Packet
Level QoS'. Each packet carries its own unique QoS. The meta data
to be transmitted to DetNet are:
- Async traffic with latency-information.
- Sync, periodic traffic
- urgency of messages
- Flowlet identification (for related packets).
This can be implemented using the HBH extension header option.
5.3. Operation and Control Network Option (OCNO)
The OCN Option (OCNO) is a hop-by-hop option that can be included in
IPv6 for OCN traffic control extensions.
0 1 2 3
0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| Option Type | Opt Data Len |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| OCNF flags | OCN-TC-Flowlet nonce | sequence |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| (bounded latency spec) |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
| (Delay variation spec) |
+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+
Figure 4: Explicit Traffic Control HBH Options
Option Type:
8-bit identifier of the type of option. The option identifier for
the OCN Option (0x??) to be allocated by the IANA. First two bits
will be 00 (skip over this option and continue processing the
header.)
Option Length:
8-bit unsigned integer. Multiple of 8-octets.
OCN Function Flags:
Some flags require metadata, others dont. So process flags in
order, if the flag is off, following metadata will not be present.
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+======+===============================================+
| Flag | Description |
+======+===============================================+
| U | send message immediately. its an alarm |
+------+-----------------------------------------------+
| P | periodic packet (intervals in ~ms) |
+------+-----------------------------------------------+
| F | part of flowlet. see Nonce and seq |
+------+-----------------------------------------------+
| L | bounded latency spec provided |
+------+-----------------------------------------------+
| R | Reliability with no packet loss tolerance |
+------+-----------------------------------------------+
| V | Delay variation with no packet loss tolerance |
+------+-----------------------------------------------+
Table 1
Flowlet nonce:
16-bit. identifies that a packet is associated to group of packets
and shares fate.
Flowlet sequence:
8-bit. sequence to be used for ordering with in flowlets.
Bound Latency Spec:
32-bit. Encodings, to be defined.
16-bit (upper bound), 16-bit (lower-bound). This field will
provide upper and lower latency bounds describing the the latency
bounds in milliseconds corresponding to the packet.
Delay Variation Spec:
16-bit. for synchronous stream, delay variation tolerance in ms.
6. IANA Considerations
TBD
7. Security Considerations
See section on security above.
8. Acknowledgements
9. References
9.1. Normative References
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[DETNET-DP]
Finn, N., Thubert, P., Varga, B., and J. Farkas,
"Deterministic Networking Architecture", RFC 8655,
DOI 10.17487/RFC8655, October 2019,
<https://www.rfc-editor.org/rfc/rfc8655>.
[DETNET-IP]
Varga, B., Ed., Farkas, J., Berger, L., Fedyk, D., and S.
Bryant, "Deterministic Networking (DetNet) Data Plane:
IP", RFC 8939, DOI 10.17487/RFC8939, November 2020,
<https://www.rfc-editor.org/rfc/rfc8939>.
[RFC8939] Varga, B., Ed., Farkas, J., Berger, L., Fedyk, D., and S.
Bryant, "Deterministic Networking (DetNet) Data Plane:
IP", RFC 8939, DOI 10.17487/RFC8939, November 2020,
<https://www.rfc-editor.org/rfc/rfc8939>.
[RFC9055] Grossman, E., Ed., Mizrahi, T., and A. Hacker,
"Deterministic Networking (DetNet) Security
Considerations", RFC 9055, DOI 10.17487/RFC9055, June
2021, <https://www.rfc-editor.org/rfc/rfc9055>.
9.2. Informative References
[FACTORY] Westphal, C., Makhijani, K., Dev, K., and L. Foschini,
"OCN Use Cases for Industry control Networks", Work in
Progress, Internet-Draft, draft-wmdf-ocn-use-cases-00, 7
July 2022, <https://datatracker.ietf.org/doc/html/draft-
wmdf-ocn-use-cases-00>.
[NIST-OT] "Risk management framework for information systems and
organizations:: a system life cycle approach for security
and privacy", National Institute of Standards and
Technology report, DOI 10.6028/nist.sp.800-37r2, December
2018, <https://doi.org/10.6028/nist.sp.800-37r2>.
[OCN-MODEL]
Makhijani, K., Faisal, T., and R. Li, "Operations and
Control Networks - Reference Model and Taxonomy", Work in
Progress, Internet-Draft, draft-km-intarea-ocn-00, 2 July
2022, <https://datatracker.ietf.org/doc/html/draft-km-
intarea-ocn-00>.
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[PTP-GRID] "IEC/IEEE International Standard - Communication networks
and systems for power utility automation – Part 9-3:
Precision time protocol profile for power utility
automation", IEEE standard,
DOI 10.1109/ieeestd.2016.7479438, August 2016,
<https://doi.org/10.1109/ieeestd.2016.7479438>.
[VIRT-PLC] Makhijani, K. and L. Dong, "Virtualization of PLC in
Industrial Networks - Problem Statement", Work in
Progress, Internet-Draft, draft-km-iotops-iiot-frwk-02, 5
March 2022, <https://datatracker.ietf.org/doc/html/draft-
km-iotops-iiot-frwk-02>.
Authors' Addresses
Kiran Makhijani
Futurewei
Email: kiran.ietf@gmail.com
Tooba Faisal
King's College London
Email: tooba.hashmi@gmail.com
Richard Li
Futurewei
Email: richard.li@futurewei.com
Cedric Westphal
Futurewei
Email: cedric.westphal@futurewei.com
Makhijani, et al. Expires 14 September 2023 [Page 18]
