Enhanced Use Cases for Scaling Deterministic Networks

Enhanced Use Cases and Network Requirements

Industrial Internet

Use Case Description In the industrial internet, the entire industrial process can be roughly divided into research and development design, production manufacturing, operation and maintenance services. The typical application prospects of deterministic networks mainly include ultra-high definition video, cloud-based robots, remote control, machine vision, and cloud-based AGV. The scenarios such as machine vision, AGV intelligent control, remote control, and AR assisted robotic arm control demand deterministic requirements.

Machine Vision The machine vision system needs to achieve real-time remote monitoring function, which requires high-speed and large connectivity characteristics. It can monitor the production process execution management system (MES) of manufacturing enterprises through mobile and portable terminals without entering the workshop, and obtain the operating status of the visual inspection system, such as normal operating time, effective operating time, fault cause etc. It is bandwidth sensitive and demand cloud-based deployment and wide area networks requirements. The following table shows the main network requirements of machine vision.(These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR 22.261, and 3GPP TR 22.829.)

+---------------------------------+---------------------------------+ | Machine Vision Requirement | Attribute | +---------------------------------+---------------------------------+ | Bandwidth | Real time upload of image | | | information:>50M | | | | | One-way maximum delay | 10 ms | | | | | Availability | 99.99% | +---------------------------------+---------------------------------+

Remote Control Remote control can ensure personnel safety, improve production efficiency, and achieve assistance from multiple production units. In order to achieve the effect of remote control, the controller needs to send status information to the controller through a communication network based on remote perception. The controller analyzes and makes decisions based on the received status information, and then sends corresponding action instructions to the controller through the communication network. The controller executes the corresponding actions based on the received action instructions, completing the remote control process. In order to guarantee control effectiveness, communication network latency, jitter, and reliability are even more important. The typical application is cloud-based PLC (Programmable Logic Controller). It is jitter sensitive and cloud-based PLC demand wide area networks requirements. The following table describes requirements of Cloud-based PLC. (These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR 22.261, and 3GPP TR 22.829.)

AGV Intelligent Control Automated Guided Vehicle (AGV) is an intelligent device widely used in highly automated places such as factory workshops, airports, ports, freight warehouses, etc. It generally consists of three parts: walking, navigation, and control systems. The automated AGV is equipped with a camera to capture the scene in front of the vehicle and upload it to the MEC and navigation system in real-time through a 5G module for image analysis and route planning, achieving fully automated logistics transportation. AGV has a certain driving speed and is often used in cluster operation scenarios. Therefore, a network connection with high deterministic delay and jitter is required to transmit control signals. The following table describes requirements of AGV intelligent control.(These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR 22.261, and 3GPP TR 22.829.)

AR Assistance With the intelligent and networked transformation and upgrading of industrial manufacturing equipment, more and more AR assisted intelligent robots will be used in advanced manufacturing. At the same time, there are scenarios where multiple robot systems work together, such as welding, stamping, etc. The robotic arm is the most widely used automated mechanical device in the field of robotics technology, in areas such as industrial manufacturing, medical treatment, entertainment services, military, semiconductor manufacturing, and space exploration. The more axis joints of the AR assisted robotic arm, the higher the degree of freedom, and the larger the angle of the operating range. The following table describes requirements of AR Assistance. (These metrics are based on 3GPP Standard 3GPP TS 22.104, 3GPP TR 22.261, and 3GPP TR 22.829.)

Requests to the IETF

Real-time remote monitoring, which requires high-speed connectivity
Cloud-based deployment, which requires transmission through heterogeneous networks
Cloud-based centralized management
Remote control is jitter sensitive, e.g. less than 100us
Industrial camera images with high definition, with little or no compression, which requires high bandwidth
Low end-to-end delay requirements differ from applications and services, such as 10ms and 20ms

High Experience Video

Use Case Description High Experience Video refers to video content that delivers an exceptional viewing experience through advanced technologies and production techniques. It demands high-quality transmission to ensure that the content is delivered without compromising its integrity and impact. High Experience Video relies on deterministic networks to deliver the best possible viewing experience, which requires a combination of low latency, low jitter, high bandwidth, and high reliability. The typical scenarios of High Experience Video involve applications that have high requirements for video quality, transmission speed, and user experience such as cloud VR and AR, cloud games and cloud live streaming.

Cloud VR and AR The key feature of Cloud Virtual Reality/Augmented Reality (Cloud VR/AR) is that content is on the cloud and rendering is on the cloud. By utilizing powerful cloud capabilities, VR/AR user experience is improved and terminal costs are reduced. VR/AR will quickly enter Cloud VR/AR to promote the rapid popularization of VR/AR services. Cloud AR/VR services exhibit strong latency sensitivity, and different levels of experience require differentiated certainty. Cloud VR/AR rendering and streaming latency are divided into three parts: cloud processing, network transmission, and terminal processing. Cloud VR/AR operation latency is divided into cloud rendering latency and terminal secondary rendering and refresh rendering processes. The following table describes requirements of Cloud VR/AR. (These metrics are based on 3GPP TR 22.261).

Cloud Games Cloud Game is an online gaming technology based on cloud computing technology. Cloud gaming technology enables lightweight devices with relatively limited graphics processing and data computing capabilities to run high-quality games. In cloud game scenarios, game related computing is not run on the user terminal, but on a cloud server, which renders the game scene as a video and audio stream and transmits it to the user terminal through the network. The user's cloud gaming experience relies on a high-quality, low latency network environment. The following table describes requirements of Cloud Games:

+----------------------+-----------+---------------------+----------------+ | Requirement | Bandwidth |One-way maximum delay|Video resolution| +----------------------+-----------+---------------------+----------------+ | Junior level | >8Mbps | 150ms |720P | +----------------------+-----------+---------------------+----------------+ | 3A professional level| >12Mbps | 60ms |1080P | +----------------------+-----------+---------------------+----------------+ | Level of esports | >40Mbps | 60ms |4K | +----------------------+-----------+---------------------+----------------+

Cloud Live Streaming For scenarios such as concerts, press conferences, sports events, and live events, cloud live streaming uses 5G uplink high bandwidth to transmit 8K/VR videos. Combined with various applications such as video analysis based on live streaming services, character and scene recognition, real-time presentation of athlete and event data, and VR live streaming interaction, it provides a brand new and rich event viewing experience. The following table describes requirements of Cloud live streaming:

+------------------------+---------------------+ | 8K live streaming | Attribute | | 8K video feedback | | +------------------------+---------------------+ | Bandwidth | upstream>100Mbps | | | | | One-way maximum delay | 200ms | | | | | Availability | 99.9% | | | | | Frame rate | 60 | +------------------------+---------------------+

Requests to the IETF

High requirements for video quality and transmission speed
Cloud processing with real-time interaction
Cloud-based deployment, which requires transmission through heterogeneous networks
No jitter requirements
Packet loss requirement is less than 0.001%
End-to-end delay requirements differ from applications and services, such as 8ms, 15ms, 50ms, 150ms, 200ms and so on

Intelligent Computing

Use Case Description Intelligent computing refers to the integration of artificial intelligence (AI) techniques with computational methods to enhance the performance, efficiency, and capabilities of computing systems. It involves the use of algorithms, machine learning models, and other AI approaches to solve complex problems, analyze large datasets, and improve decision-making processes. Intelligent Computing has specific requirements for deterministic networks to ensure reliable and predictable performance such as predictable latency, low packet loss rate, high throughput and reliability. The typical scenarios involve applications such as AI-based scientific research and autonomous vehicles and so on.

Scientific Research Intelligent computing is used to provide computing and data analysis capabilities, which are crucial for handling large-scale scientific simulations and datasets such as astronomy, climate science, and bioinformatics. In scientific research, a large amount of computing power resources such as CPU, GPU, memory, and other P-level or higher are usually required. The network needs to provide services for data volume of 10G to 100G or above, which requires high bandwidth, high reliability and high throughput with ultra-low packet loss. Many applications in scientific research, such as remote observations, real-time data analysis, and distributed computing, require networks to provide stable low latency and high reliability. It must provide millisecond or even microsecond level latency and jitter guarantees. For example, in nuclear fusion experiments, the carrier network is required to have 99.999% availability.

Autonomous Vehicles Intelligent computing is used in the development of self-driving cars, which rely on AI algorithms for perception, decision-making, and control. Autonomous vehicles refers to the technology of vehicles that are capable of navigating without the need for human input such as identifying other vehicles, pedestrians, and traffic signals. It relies heavily on deterministic forwarding to ensure safe, efficient, and reliable operation. It is also challenging for big data management of autonomous driving. Vehicles record data from 4K HD cameras, laser scanners, and radars on the road. Each vehicle can generate 80TB of data per day, which requires data-intensive transmission. V2X (Vehicle-to-Everything) is a fundamental component of the autonomous driving ecosystem, providing the necessary communication backbone that enables vehicles to interact with their environment in a safe and efficient manner. V2X provides the communication infrastructure that enables vehicles to exchange information with each other (V2V), with roadside infrastructure (V2I), with pedestrians (V2P), and with the network (V2N). This exchange of information is crucial for autonomous vehicles to make informed decisions, improve navigation accuracy, and enhance overall road safety. The following table describes requirements of 5G V2X which is divided into four scenarios. (These metrics are based on 3GPP TR 22.886)

+----------------------+---------------------+--------------+ | Requirement | Communication Delay | Availability | +----------------------+---------------------+--------------+ | Vehicles Platooning | 10~25ms | 99%~99.99% | +----------------------+---------------------+--------------+ | Extended Sensors | 3~100ms | 99%~99.999% | +----------------------+---------------------+--------------+ | Advanced Driving | 3~100ms | 99%~99.999% | +----------------------+---------------------+--------------+ | Remote Driving | 5ms | 99.999% | +----------------------+---------------------+--------------+

Requests to the IETF

Real-time communication
Data-intensive transmission with high throughput and ultra-low packet loss
Low bounded latency, such as us~ms
High availability, such as 99.999%

Use Case Common Themes

Differentiated Deterministic Requirements Classification and characteristics has been summarized from the requirements of use cases as described in and this documents. Seven levels of typical applications have been defined including on-site production control, remote control, production monitoring, production collection, video AI, AR/VR high experience video and intelligent computing. Different levels of applications differ in the network ranges and SLAs requirements such as bounded latency, jitter, bandwidth, availability and isolation. The following table summarizes deterministic requirements of industrial internet, cloud video and intelligent computing applications, etc.

+---+------------+--------------------+---------------------------------------------------------+ | | Use Case | Typical | Differentiated Deterministic Requirements | | | | Applications +----------+----------+---------+-------------------------+ | | | |Bandwidth | Delay | Jitter |Packet Loss| Availability| +---+------------+--------------------+----------+----------+---------+-----------+-------------+ | 1 |Industrial |Machine Vision | Low | Low | N/A | N/A | Medium | | |Internet | | | | | | | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |Remote Control | Low | Low |Ultra-low| N/A | High | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |AGV Control |Low~High |Low~Medium| N/A | N/A | Ultra-high | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |AR Assistance | Low | Low |Ultra-low| N/A | High | +---+------------+--------------------+----------+----------+---------+-----------+-------------+ | 2 |High |Cloud VR and AR |Medium | Low | N/A | Ultra-low | N/A | | |Experience | | ~High | | | | | | |Video | | | | | | | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |Cloud Games | Low | High | N/A | N/A | N/A | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |Cloud Live Streaming| Medium | High | N/A | N/A | Medium | +---+------------+--------------------+----------+----------+---------+-----------+-------------+ | 3 |Intelligent |Scientific Research |Ultra-high| Low | N/A | Ultra-low | Ultra-high | | |Computing | | | | | | | | | +--------------------+----------+----------+---------+-----------+-------------+ | | |Autonomous Vehicles |Ultra-high| Low | N/A | Ultra-low | Ultra-high | +---+------------+--------------------+----------+----------+---------+-----------+-------------+ Since the DetNet applications differ in their requirements, it demands specific desired behavior and different services requires differentiated DetNet QoS. The classification of the deterministic flows within different levels should be taken into considerations. It is required to provide Latency, bounded jitter and packet loss dynamically and flexibly in all scenarios for each characterized flow. For example, as the figure shows, the services can be classified into 4 types and DetNet applications and related deterministic behaviors are differentiated within each type.