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Scale 5G with Edge Computing
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August 3, 2021 Blog

 

Authored by: Derek Li, Principal Architect at Red Hat

The 5G mobile network is the latest global wireless standard developed by 3GPP. While 4G networks provide connectivity to most current cell phones, 5G can enable connectivity for an expanded set of devices, from machines to vehicles. In this article, we will share some advantages of 5G, provide an overview of edge computing and look at some potential use cases.

What challenges can 5G address?

5G has been designed to meet many challenging requirements, including:

  • Significantly higher throughput (up to 20 Gbps peak data rates based on International Mobile Telecommunications-2020 (IMT-2020) requirements) in mobile broadband, such as 4K videos streaming or virtual reality (VR).
  • Ultra-low latency (less than 1 millisecond) for real-time communications, such as surveillance drone manoeuvring.
  • Massive network capacity, with plans to exceed the number of connected devices per unit area by over 100x compared with 4G/LTE technologies.
  • A more uniform user experience and more users, i.e. higher reliability in crowded areas such as stadium and sports events.
  • Improved energy efficiency, including reducing power consumption and the delivery of cellular Internet of Things (IoT) devices that can last for more than 10 years.
  • The new 5G core network follows a Service-Based Architecture (SBA), which allows for the adoption of cloud-native technologies and open-source software into telecom networks and brings in more collaboration, innovation, and openness.

Figure 1: Use cases for 5G

What is edge computing?

It is hard to get the full picture of 5G without understanding edge computing. Edge computing is computing that takes place at or near the physical location of either the user or the source of the data, which results in lower latency and saves bandwidth.

Effectively, edge computing is a concept that enables services to be hosted close to the service consumers (e.g., subscribers, machines, and devices). Being closer provides benefits, including significantly reducing end-to-end latency, decreasing load and saving cost on the backhaul transport network and enhancing data privacy (i.e., private 5G use case). The edge computing paradigm is the only way to realise the latest 5G URLLC use case, and it also addresses many challenging mobile network issues in 5G technologies.

The Emerging Edge Computing Use Cases of 5G

Edge computing is the key to achieving the promise of many new 5G use cases, including virtual and augmented reality (VR/AR), IoT, Industrial IoT, autonomous cars and drones, real-time multiplayer gaming, and recently, the deployment of open Radio Access Network (open RAN) which is possibly the first prevailing edge computing use case in 5G mobile network. Some recent references can be found in these releases from Red Hat:

Figure 2. Sample open RAN architecture

Low Latency Applications and Edge Cloud Platform

For the incoming low latency and real-time use cases, such as VR/AR, autonomous and connected vehicles, drone control, telesurgery and medical robotic instruments, and real-time multiplayer online gaming, the edge computing paradigm is the most effective way to ensure the low latency and also minimise the backhaul bandwidth and cost.

As mobile operators cannot build all the use cases themselves, they will need to attract partners and developers to build an optimised ecosystem on top of their edge cloud. Independent software vendors (ISV) and enterprise developers demand a platform that can help abstract the network complexity, including making use of the mobile network capabilities (e.g., user location, SIM-based authentication, prepaid/postpaid payment mechanism, etc.) in a more secure way.

Without the edge cloud platform, mobile operators will fall back to the “dumb pipe” utility model and continue suffering from the declined average cellular data price (e.g., about 10% year-over-year declination for the estimated average price of cellular data per gigabyte from 2018 to 2023 in US). Figure 2 describes the potential roles that a telco operator can play from the Edge Cloud value chain perspective, such as Infrastructure Provider, Edge Service Provider or overall Service Provider.

Figure 3: Roles operators can play in the edge cloud value chain

To meet the needs of various edge computing scenarios, an edge computing solution should support hybrid workloads of virtual machines (VMs), containers, bare-metal nodes running network functions, and Artificial Intelligence and Machine Learning (AI/ML) workloads in microservices architectures. This solution needs to have operational simplicity by automating bare-metal provisioning, application onboarding, tenants and workload isolation, software-defined networking and storage, as well as management and orchestration.

Red Hat considers edge cloud and computing as an integral part of its open hybrid cloud strategy, and works to provide a consistent experience for everyone from the application developer to the infrastructure operations team. This consistency should be end-to-end, from edge devices, networks, up to the centralised data centre to maximise potential. Hybrid cloud strategy and approach provide sanity to what would otherwise be chaos across a technology ecosystem.

Outlook on the future of edge computing

Although 5G is relatively new, edge computing may play a significant role in the 5G ecosystem. Edge computing and processing will be used to cache, analyse, and filter local content. The edge cloud can also act as an intermediary, and forward data only when needed to the core network so it can optimise the backhaul bandwidth requirement.

This decentralised approach improves resilience, provides real-time interaction, enables local content and privacy, and delivers a superior user experience. It also enables mobile operators to support more use cases and reach customers faster. Finally, it leads to differentiation and the creation of new revenue streams for mobile operators.

As 5G is still quickly evolving, it is difficult to foresee all possible developments and requirements.

Due to this, it is nearly impossible to have a single vendor that can provide a complete edge computing solution. Instead, an evolving edge computing solution will most likely be formed from multiple components by multiple vendors.

That is exactly what open source is here for. When choosing open source solutions, edge technologies work across a wide ecosystem and communities–as there is no proprietary technology stack–and removes vendor lock-in.

The future of edge computing platforms has to be innovative, hybrid, and open, and working open source communities may power the next era of edge cloud computing technology.

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