IIoT L. Geng
Internet-Draft China Mobile
Intended status: Standards Track M. Zhang
Expires: May 3, 2018 M. McBride
B. Liu
Huawei
October 30, 2017
Problem Statement of Edge Computing beyond Access Network for Industrial
IoT
draft-geng-iiot-edge-computing-problem-statement-00
Abstract
This document introduces the concept of Beyond Edge Computing (BEC)
which brings edge computing capabilities down to the level of
customers' premises for industrial IoT use cases. The purpose of the
document is to discuss the general problem statement of BEC including
capabilities, and use cases. Potential technical gaps in IETF
problem scope that are related to BEC are also evaluated.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 3
1.2. Terminology . . . . . . . . . . . . . . . . . . . . . . . 3
2. The Concept and Capabilities of Beyond Edge Computing . . . . 3
2.1. Relationship between BEC and and Cloud Computing . . . . 5
3. Reference Architecture . . . . . . . . . . . . . . . . . . . 5
4. Use Cases of BEC . . . . . . . . . . . . . . . . . . . . . . 7
5. Gap Analysis . . . . . . . . . . . . . . . . . . . . . . . . 9
6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 10
7. Security Considerations . . . . . . . . . . . . . . . . . . . 10
8. Acknowledgement . . . . . . . . . . . . . . . . . . . . . . . 10
9. Normative References . . . . . . . . . . . . . . . . . . . . 10
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 11
1. Introduction
Edge computing is an important network architecture particularly in
the support of Industrial verticals such as Energy, Manufacturing,
Healthcare, Mining and Smart City/Buildings. Edge computing will
provide local compute, storage and connectivity services particularly
for latency and bandwidth sensitive applications. There are several
organizations which are working on edge computing definition and
architecture with various emphases. For instance, ETSI MEC
(previously mobile edge computing and now multi-access edge
computing) looks at edge computing from the perspective of the edge
of the provider network. It also has a successive convention of
focusing on cellular network requirements. The Industrial Internet
Consortium (IIC) and Edge Computing Consortium (ECC) works on edge
computing in a more general view of industrial IoT, where edge
computing nodes even closer to verticals (i.e. the very first hops
where the service is connected to the network). Typically, the edge
computing nodes are located at customers' premises. However, IIC and
ECC are not standard organizations and they rely on communities such
as IETF to provide protocols and API definitions for their
architectural use especially as Operation Technology (OT),
Information Technology (IT) and Communication Technology (CT)
converge.
Edge computing concepts have been presented in various groups within
the IETF/IRTF. The edge computing topic, similar to cloud computing,
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is much too broad to tackle within the IETF. There are specific
protocol/interface areas, however, that can be worked on in the IETF
once we identify a specific area of focus. BEC is one of the
specific area which looks at edge computing from the industrial
verticals such as factory, hospital, power and city/ building
perspective and down to the level of local edge support for sensors,
engines, pumps and machinery.
A simple example, of BEC, is factory equipment having connected
sensors which are generating data and sending to the equipment within
an edge computing environment. One sensor, connected to this
equipment, could generate an event, such as overheating, and a
connected actuator could quickly increase fan span or reduce engine
speed depending upon the data within the local edge computing node.
This type of event is being controlled today within closed industrial
command and control protocols. But what is not generally available
is the ability for open edge computing equipment to generate
predictive maintenance and command and control across factories,
verticals and into the cloud. This is where we see a gap in
standards definitions and an opportunity for new protocols and
interfaces, in which IETF could play a particularly important role.
1.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].
1.2. Terminology
o BEC - Beyond Edge Computing, a concept of edge computing where the
edge computing devices are deployed directly at customers'
premises so that beyond the access network of a service provider.
2. The Concept and Capabilities of Beyond Edge Computing
Beyond Edge Computing (BEC) looks at the on-site intelligent
evolution of industrial verticals. It brings the computing
capability down to the level of customer premises where devices are
managed by customers therefore typically beyond the reach of access
network of a service provider.
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+-------------------------------+
| Core Data Center |
+-------------------------------+
*** Backbone
* * Network
***
+-------------------------------+
| Regional Data Center |
+-------------------------------+
*** Metropolitan
* * Network
***
+-------------------------------+
| Local Data Center/Access Point|
+-------------------------------+
*** Access
* * Network
***
+-------------------------------+
| Beyond Edge Computing |
+-------------------------------+
Figure 1: Beyond Edge Computing in the Network
Figure 1 illustrates the schematic diagram of BEC in terms of its
position in an overall network. BEC takes care of the first hop
where the service of a particular industrial vertical connects to the
network. It can be regarded as an extended intelligent connectivity
capability of a service provider's network to industrial verticals.
Meanwhile, it also expands the cloud computing ability directly to
customers' sites.
BEC has the following capabilities.
1. Heterogeneous IoT device compatibility
2. Extremely low and deterministic service latency
3. Local data pre-processing and offloading
4. Isolation of system resources
5. Offline process
6. End-to-end security
7. Distributed artificial intelligence
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8. Real-time operation
9. Unified API for multi-ecosystem edge application
10. Service isolation for network slicing
2.1. Relationship between BEC and and Cloud Computing
BEC is different from Cloud Computing in the following perspectives.
o Edge is closer to things than the Cloud, it's feasible to meet the
high reliability, bounded latency or real-time requirements of
verticals such AR/VR, automatic driving and smart manufacturing. For
Cloud Computing, the latency is regarded as a performance index. As
for Edge Computing, bounded latency is often a mandatory requirement.
o Data can be stored at the Edge which are under the control of end
users so that user's privacy can be preserved. Video surveillance,
Healthcare are typical use case scenarios for this perspective.
o Raw data can be preprocessed at the edge while only critical
information is uploaded to the Cloud. In this way, Edge Computing
promises lower communication cost than the traditional Cloud-only
architecture.
o The resources for Cloud Computing can be elastically allocated
thanks to virtualization and resource pooling. Virtualization
provides certain reliability to Cloud Computing. In comparison, the
resources are normally constrained for Edge Computing. Reliability
is sometimes realized through the redundant placement of physical
edge devices.
o The hardware and software of Cloud Computing are normally
standardized. Devices and software being used in Edge Computing can
be quite different considering various verticals are adopting Edge
Computing.
3. Reference Architecture
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+--------------------------------+
| BEC Management Platform |
| |
| +----------------------------+ | +-------------+
| | Application Management | | | |
| +----------------------------+ | | IoT |
| +------------+ +------------+ | | Cloud |
| | Device | | Resource | | | Services |
| | Management | | Management | | | |
| +------------+ +------------+ | | |
| +----------------------------+ | | |
| | SDN Platform | | +----+--------+
| +----------------------------+ | |
+--------------------------------+ |
| Management |Data
| Channel |Channel
+----------------------------------------------------+
| +-------------v-------------------+ BEC node |
| | Management Data Model | | |
| +---+-------+-------+---------+---+ | |
| | | | | | |
| | | | | | |
| | | | +------------------+ |
| | | | | +---------+ | |
| | | | | | APP | | |
| | | | | +---------+ | |
| | | | |Container/VM | |
| | | | +------------------+ |
| | | +-v----------------------------+ |
| | | | Virtualization Layer | |
| | | +------------------------------+ |
| | +-----v------------------------------------+ |
| | | API Exposure | |
| | +------------------------------------------+ |
| +---v--------------------------------------------+ |
| | Linux Kernel | |
| +------------------------------------------------+ |
| Ethernet Bluetooth PLC RF RS485 |
| WiFI FXS DI/DO RS232 |
+----------------------------------------------------+
Figure 2: The Reference Architecture of Beyond Edge Computing
Figure 2 demonstrates the reference architecture of BEC system with a
managed BEC node and a cloud-based management platform. An IoT
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gateway is the typical form of a BEC node device. Gateways always
play important role in the Cloud-Edge architecture since they are the
most popular devices where verticals are provided with various
capabilities such as computing, storage and networking. In addition,
applications for various vertical customers are developed by
themselves or third-party while deployed on demand. Giving the edge
computing ability of BEC, much of the data can be processed by
applications running on the gateway locally as required by vertical
customers. The gateways are commonly versatile protocol speakers so
that devices speaking different protocols can communicate with them.
The East-West connectivity between BEC nodes might be enabled by
various protocols such as OPC-UA, MQTT, TSN and other deterministic
Ethernet protocols, for example EtherCat, Ethernet/IP, Profinet. To
facilitate the operation of the BEC system, a central controller in
the cloud is provisioned to the customer. It mainly supervises the
device, virtulization resource and application life cycle of the BEC
node
The key requirements of BEC are in providing distribution service
entities on the customers' site (end AP, devices) to meet the growing
demand for low latency, reliable, and secure vertical industries.
The Computing, Storage, I/O isolation are remotely managed at the
edge to provide certain dedication and quality guarantees. Agile,
flexible and scalable deployment of services from operator/third
party down to the edge through software entities (VM/ Containers). A
light weight MANO like approach is needed to provide resource
provisioning and VNF deployment. A unified API definition is needed
to support the co- existence of multi-ecosystem at the BEC node. And
there needs to be the ability for the edge device to map specific
service requirements with an end to end network slice with certain
guarantees and pass the policy identification along the path to the
centralized DC.
4. Use Cases of BEC
1. Elevator Networks
Description: There are more than 15 million elevators around the
world and the daily maintenance of these elevators costs elevator
operators a large amount of revenue. An elevator usually carries
hundreds of sensors which are generating a large amount of data to be
uploaded to the cloud. The BEC nodes can preprocess the data
gathered from elevator sensors so that the volume to be uploaded to
the Cloud is greatly reduced. Based on the input from elevator
sensors, AI programs installed on BEC nodes may locally make
decisions without the intervention of the Cloud. For example, when
the noise or vibration of an elevator exceeds a certain level, the
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BEC node may notify elevator maintainers to reach this elevator and
perform maintenance or repair.
Goal: BEC nodes are deployed into elevators to gather/preprocess/
compress the data to save the communication cost. Based on the data
gathered from elevator sensors, BEC nodes can assist operators to do
predictive maintenance.
Requirements: Customized gateways operated by elevator providers. An
open platform with VMs/containers which can hold customized Apps.
These Apps are managed by elevator operators while developed by
gateway vendors or any other third parties. Various connectivities
are supported (2G/3G/LTE/eMTC/Ethernet) by BEC nodes. A central
controller to perform configuration and management of the network.
AI models are trained on the Cloud while the reasoning of these AI
models are performed at the Edge.
2. Street Lights
Description: BEC nodes are placed on street lights to act as board
routers of LLNs. BEC nodes may act as RSUs of vehicle networks.
With AI programs installed on the BEC nodes, reasoning and decisions
might be made locally at the edge. For example, BEC nodes can adjust
the lights' brightness and operating hours according to environment
parameters, providing illumination when needed while reducing power
consumption. With sensors on trash cans, BEC nodes are aware whether
a trash can is full. Trash collecting cars can communicate with the
BEC nodes to determine whether to reach a trash can to collect the
trash.
Goal: BEC nodes gather data from sensors which are used to monitor
various information (e.g., brightness, temperature, humidity) of a
district.
Requirements: BEC nodes SHOULD support ROLL [RFC] in order to join
the LLN as a board router. Various wired/wireless communication
protocols such as Radio Frequency (RF) protocols (e.g., Zigbee, WI-
SUN) and Power Line Communication (PLC) should be supported. The BEC
nodes can use 2G/3G/LTE/Ethernet to communicate with the Cloud.
3. Smart Manufacturing
Description: BEC nodes join the industrial manufacturing network and
provide the networking function. Control messages that requires
deterministic latency will be carried on this network. BEC nodes
need to support deterministic networking protocols such IEEE Time
Sensitive Networking (TSN), Profinet, Ethernet/IP, EtherCat, etc.
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The gateway can also help monitor the equipment's status, and send
out alarms or warnings when malfunction is detected or predicted.
Goal: Edge computing enables interconnection of deterministic
networks.
Requirements: BEC nodes should support industrial machine-to-machine
message bus connectivity protocols such as OPC-UA, DDS, MQTT. The
network may be configured by a central controller using Netconf/YANG.
BEC nodes should support the interconnection of heterogeneous
deterministic Ethernet protocols.
4. Smart grid
Description: BEC nodes can be deployed in three scenarios of the
smart grid. In advanced metering infrastructure (AMI), besides the
routing function, a BEC node can also act as a concentrator to
collect and aggregate the meters' data. It can also provide primary
analysis to detect theft and outage. Firewall function can be
deployed at the gateway to deal with attacks from the edge. In
distribution automation (DA), BEC nodes provide bounded latency
connection between controller and actuators such as switches and
transformers. Edge computing applications can be implemented on
these devices to monitor the status and react rapidly to faults. In
terms of micro grid, the BEC node monitors the local power generation
and storage, and helps smoothly integrate the energy generated by
photovoltaic panels and wind turbines, whose power is very unstable,
into the macro grid.
Goal: In AMI, the BEC node works as a router, firewall and
concentrator, providing data preprocess services. In DA, BEC node
enables the deterministic connection between controllers and
actuators. In micro grid, BEC node is the coordinator between
distributed and centralized generation.
Requirements: The gateway should support various wired/wireless
communication protocols, such as Power Line Communication (PLC),
Radio Frequency (RF), NB-IOT and 2G/3G/LTE. Bounded latency is
required in automation use cases. Open platforms are needed to
accommodate various applications providing data analysis, fault
detection and automation control capabilities.
5. Gap Analysis
1. Multiple Virtualization Technologies Coexistence/Coordination:
Different virtualization technologies needed to meet the various
vertical requirements. Coexistence and resource coordination is
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needed. The focus is on the edge where different types of ASICs are
found which require more input on selection.
2. Light weight Device-level management and virtual resource
management:
Netconf/YANG to be considered as a baseline interface solution.
Information and data modelling will need to be defined.
3. Framework and API for multi-ecosystem:
BEC framework for life cycle management. Unified API definition
between framework and app including Local networking, Computing,
Storage, OAM, UNI IO management and event-message management.
4. Runtime Updates
BEC nodes are commonly deployed to run for a long periods of time
without downtime. Even during the update of configuration, software
or firmware, the BEC nodes are required to serve the network with no
interruption. For mesh-based networks, there might be some devices
which are in sleeping mode. IP multicast protocols are not
applicable here [draft-iab-iotsu-workshop-00]. Multicast Protocol
for Low-Power and Lossy Networks (MPL) [RFC7731] should be used.
6. IANA Considerations
N/A
7. Security Considerations
Security considerations will be a critical component of IIoT edge
computing particularly as intelligence is moved to the extreme edge.
8. Acknowledgement
The authors would like to thank Sami Kekki for his feedback on this
draft.
9. 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>.
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Authors' Addresses
Liang Geng
China Mobile
Email: gengliang@chinamobile.com
Mingui (Martin) Zhang
Huawei
Email: zhangmingui@huawei.com
Mike McBride
Huawei
Email: michael.mcbride@huawei.com
Bing Liu
Huawei
Email: remy.liubing@huawei.com
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