Optimizing data upload with 5G exposure: Key benefits for the automotive industry
- Data transmission using mobile networks has become a key concern for vehicle manufacturers due to high costs and difficult efficiency controls.
- Ericsson exposure of 5G network status and analytics allows CSPs to avoid network congestion and offload data from the vehicles.
Driving towards the future, the ambition of the automotive industry for fully connected vehicles
The future of cars is poised for a major transformation with the ambition of achieving fully connected vehicles. This advancement brings a multitude of benefits, including autonomous driving, enhanced infotainment and personalization, improved traffic security and more efficient traffic management. To enable this future, distributed edge computing plays a crucial role by decentralizing processing and bringing data closer to vehicles. However, managing vast amounts of data and ensuring its integrity and security remain key challenges. Communication service providers (CSPs) have an opportunity to offer attractive data-transfer bundles and optimize network resources through Network Analytics Exposure. This innovative solution opens the door to a range of possibilities across industries and holds the potential for future 5G monetization. The future of cars is not just about transportation—it's about creating a seamlessly connected experience that revolutionizes our way of life. Below we’ll explore some of the main questions we are asked by CSPs in relation to connected vehicles.
- Firstly, let’s look at the benefits and values of fully connected vehicles: Autonomous driving: By exchanging data with other vehicles, traffic infrastructure, and cloud-based systems, connected vehicles can contribute to the development of autonomous driving which have the potential to revolutionize transportation by improving safety, reducing congestion, and optimizing traffic flow.
- Infotainment and personalization: Connected vehicles can offer advanced infotainment systems that provide access to music streaming, internet radio, podcasts, and other entertainment options. This can also be personalized to remember driver preferences, adjust climate control settings, and even provide personalized recommendations based on driving habits and preferences.
- Traffic security: It can offer various safety features, such as collision detection, automatic emergency braking, lane departure warning, and adaptive cruise control. These technologies can help reduce accidents and enhance overall road safety.
- Traffic management and efficiency: Generating vast amounts of data about driving patterns, road conditions, and vehicle performance. This data can be analyzed to gain insights that improve traffic management leading to more efficient transportation systems.
Why is distributed edge architecture crucial for enabling connected cars?
The distributed edge architecture is one of the key pillars in enabling connected vehicles. The distributed edge architecture decentralizes the cloud and moves the processing close to the source of the data. This addresses the challenge of managing vast amounts of data. It also ensures data integrity, focusing on authentication of the car and network, secure communication between the vehicle and the network, and impeccable time synchronization. These factors play a vital role in establishing a robust and reliable connected vehicle ecosystem. The distributed edge architecture is one of the key pillars in enabling connected vehicles. It decentralizes the cloud and moves the processing close to the source of the data. By decentralizing the cloud and bringing processing closer to the data source, the distributed edge architecture addresses the challenge of managing vast amounts of data. It also ensures data integrity by focusing on authentication of the car and network, secure communication between the vehicle and the network, and impeccable time synchronization. These factors play a vital role in establishing a robust and reliable connected vehicle ecosystem.
To ensure services remain effective for millions of vehicles, it’s essential that the network and computing systems processing the data can efficiently handle the increasing amount of uplink data. Without the necessary adaptation, it becomes impossible to maintain high-quality services. Therefore, the implementation of Distributed Edge Computing is a solution that places the processing of data closer to the vehicles. This approach reduces the amount of data transmitted and enables the ecosystem to deploy and introduce newer, next-generation service offerings
The vehicle application deployed using a distributed architecture requires different types of capabilities from the network, such as the discovery of the optimal application server on the edge site with the vehicle application. If the discovery of such an optimal application is done using network analytics, it will bring more benefits.
Exposure also plays a significant role in this architecture, with embedded capabilities in exposure products such as 5G Network Exposure Function (NEF) and edge exposure. The 5G NEF facilitates the subscription to the Network Data Analytics Function (NWDAF) and exposes these analytics to the application to improve data collection and processing. Meanwhile, edge exposure facilitates the registration of edge application servers
During this year's Mobile World Congress (MWC 2023), a demo titled "Vehicle to Cloud (V2C) powered by exposure and analytics" was showcased to visitors. The demo was a representation of a proof of concept (PoC) undertaken by Ericsson in collaboration with a leading car manufacturer. It utilized Ericsson's 5G exposure products to expose network analytics to the application server of the car manufacturer, demonstrating how analytics data can be monetized and bring benefits to vehicle applications. Specifically, the PoC showcased the ability to predict congested locations for optimized data transfer and efficient utilization of network resources, highlighting the potential advantages for vehicle applications.
Why is data collection and processing important for the automotive industry?
Within the scope of V2C, this blog specifically highlights the following targeted services: infotainment services, driving behavior monitoring, augmented reality dashboards, real-time remote control, and automated lane change. These services necessitate data collection and processing, which were integral parts of the demonstrated PoC. It is worth mentioning that while there is potential for generating additional data from a vehicle, this blog will not cover those aspects.
Congestion was an important focus on the PoC because the busy hours of 5G edge network vary by geographical areas. For example, during working hours, the 5G network in the central city area is busy, while the outer suburbs or residential areas are idle. Therefore, it has become an important issue for the automobile industry to consider the reasonable use of 5G network resources and edge computing resources based on the requirements of different services for business service quality.
This is particularly true when it comes to data collection and processing, the biggest challenges brought to the automotive industry by services such as remote driving and real-time mapping (to synchronize and display info from multiple sources in real-time providing ‘living’ maps for autonomous vehicles). If all the data is transferred to the data center, the reliability of the data can be ensured. But if the transmission bandwidth is occupied, then the processing delay is increased.
For a long time, the automotive industry has been looking for a cost-efficient data bundle from CSPs. However, CSPs do not see a business case to give discounted rates for automotive industry. For them it is usual use of their data plans.
To visualize this challenge, each car produces an average of four gigabytes of data per day, and the number of connected vehicles is expected to grow to about 100 million globally. Most of this data will be processed in the cloud, and a cost-efficient broadband bundle is required to send this data. Data volume transmitted between vehicles and the cloud will be ~100 petabytes (100 million Gigabytes mainly generated from video streams for cruise assist, images for high-definition maps and electronic control unit data) per month.
In the automotive industry, the life cycle of a vehicle corresponds to the life cycle of various services that the vehicle utilizes. Among these services, some consume a significant amount of network bandwidth. As the number of connected vehicles grows, the data consumption per vehicle also increases. It is assumed that the amount of data will increase in proportion to the square of the number of connected vehicles. Additionally, different automotive services, such as video streams for cruise assist or images for high-definition maps, have varying quality of service requirements.
What are the key opportunities for operators in addressing these challenges in the automotive industry, and how can a solution be formulated?
These challenges and use cases present an opportunity for service providers to address the automotive segment by offering attractive data transfer bundles.
Network Analytics Exposure is one of the four major categories of network exposure functionalities envisioned by 3GPP. The analytics exposure capability allows an external party to fetch or subscribe/unsubscribe to analytics information generated by the 5G System. NEF supports the exposure of NWDAF analytics as specified in 3GPP TS 23.288.
Optimizing the capacity usage is achieved via the network analytics report capability that is used to enable edge computing system to subscribe to user plane congestion to control the traffic routing of service data, utilize network resources in timely and efficient manner and to improve the service experience of network users.
CSPs can monetize the idle network resources and avoid congestion while utilizing the idle network capacity. In practice the vehicle will pause non-time-critical data upload when a vehicle is in a cell that is predicted to become congested and resume data upload when a vehicle is in a cell that is not predicted to become congested.
To tackle this challenge, the exposure control solution is achieved through the management of real-time services and background data transfer, resulting in a streamlined process. The network status can be shared with the automotive company, and analytics are available to assist in predicting the network's status. Traffic growth is effectively managed in a sustainable way by utilizing idle network resources.
Benefits and use cases of optimized data upload
There are numerous benefits to using exposure and network analytics in the context of optimized vehicle data upload, which can be summarized in three key points:
- Network status analytics enable the automotive industry to utilize network resources in an optimal manner.
- With edge exposure, application providers can be directed to the appropriate application server at the right time. For instance, in congested network conditions, the edge exposure server guides the application to the specific application server it should interact with.
- Prepare for use cases involving seamless application context transfer, ensuring that users do not perceive any difference in their experience when the application on their device starts communicating with another application server on the edge due to device mobility.
As a summary, this use case is explored together with by a leading vehicle manufacturer in the automotive industry and is also aligned and reported to Automotive Edge Computing Consortium (AECC). It involves the exposure of analytics reporting capability, which demonstrates the potential impact that can be achieved. By extending the exposure to the remaining pillars, such as monitoring capability, provisioning capability and policy/charging capability, even greater possibilities and benefits can be unlocked.
Exposure is an innovative solution that could pave the way for a multitude of use cases across different industries, and a door opener for 5G monetization in the future.
Finally, the network and service exposure require entering new business models like B2B and B2B2C, B2C2X, B2D2X, B2B2X where the application partner consumes API directly. Examples of these models include:
- B2C: where operator launches new service utilizing network capabilities via APIs towards consumers; such as extended reality, low latency gaming, personalized ads within streaming applications or gaming platforms that are connected to the internet
- B2B: where operator launches new service utilizing network capabilities via APIs towards businesses; such as connected vehicles or connected drones for surveillance
- B2D: where operator make their APIs available in a marketplace for developers to enable creation of new services for the ecosystem
- B2A: where operator exposes to aggregator and aggregator offers them further to application providers; such as offering a uninterrupted unified communication service and video calls for a company across one country
All business models or use cases are various ways of monetizing the same capabilities in multiple ways.
This justification supports the investments in 5G Core, which includes features like exposure and network slicing, making 5G and 5G Advanced the game changers for future CSP revenues. These enhanced network capabilities could serve as the enabler for future monetization opportunities.
Read more about network exposure
Read more about edge exposure
Read more about network data analytics function (NWDAF)
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