Edge network automation, optimization, intelligence, and implementation highlighted in 5G Americas white paper
Edge computing is a fundamental part of the 5G ecosystem that provides network data processing and storage close to the end users, typically within or at the boundary of operator enabled networks. Today, 5G Americas, the voice of 5G and LTE for the Americas announced the publication of a new white paper entitled “5G Edge Automation and Intelligence” which details the convergence of 5G, edge computing, and artificial intelligence (AI), allowing 5G networks to deliver new services and capabilities more efficiently.
Chris Pearson, President of 5G Americas, said, “Edge computing and AI are a dynamic duo of integral technologies for 5G that will enable a plethora of use cases, which enable 5G networks to reach their full potential. 5G reduces the radio network latency significantly, while edge computing places compute and storage within the telco infrastructure resulting in end-to-end latency reduction. This will positively impact the experience of enterprises and consumers alike.”
“5G Edge Automation and Intelligence” identifies optimization and automation strategies for both 5G network and edge computing, as well as the leveraging of Artificial Intelligence/Machine Learning capabilities. Additionally, the paper covers how 5G network and edge computing enable low latency, high reliable intelligence in edge applications. It provides detailed information on potential use cases for autonomous industrial solutions, smart transport, energy, connected health, digital twins – and more. The white paper includes the technical capabilities of 5G and edge computing, where the intelligence of 5G network and edge computing can achieve groundbreaking results.
The white paper is a comprehensive guide for the exploration of intricate and complex challenges in the implementation of intelligence in 5G edge networks. It provides recommendations on bringing together expertise from multiple backgrounds for the automation and optimization of 5G networks to serve future intelligent service and application demands.
“5G Edge Automation and Intelligence” examines the following areas:
- 5G Edge Automation: background on closed-loop automation and intelligent decision-making, industry landscape and standardization efforts including 3GPP standards, Open RAN, open source, distributed data collection, normalization, real-time processing, context discovery, network slicing and dynamics, architectural directions for automation at the edge, and system recommendations for ML-based automation
- 5G Edge Optimization, Intelligence, and Analytics: envisioned features and key technologies like artificial intelligence, multi-access for the 5G edge, situational network at the edge, situation-aware transport layer protocols, joint optimization of communication and computing, and distributed learning at the edge
- Application of 5G Edge Automation and Edge Intelligence: autonomous industrial solutions, intelligent transport systems, smart energy, smart homes, connected health, enabling location information, cloud and edge gaming, and scalable digital twin technologies
Meryem Simsek, Lead Scientist, VMware, and technical working group co-leader for this 5G Americas white paper said, “The ultimate goal of the unique symbiosis between 5G and edge involves increased performance guarantees, enhanced workload balancing, improved processing capabilities and performance via 5G edge automation and optimization, with greatly reduced human intervention.”
Clark Chen, Senior Staff Engineer and Research Manager at Intel, co-leader for this white paper, agreed, “Carriers are embracing AI/ML technology to deliver the promise of 5G and increased levels of automation in the network. The convergence of communication and computing is creating innovative opportunities to deploy and integrate 5G, edge artificial intelligence and cloud capabilities. This can help address a diverse set of use cases that ultimately deliver better business outcomes across a range of industries.”
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