Despite the COVID-19 pandemic, emerging markets are seeing tremendous growth and transformation, thanks to 5G's support for heterogeneous mobility networks with advanced distributed cloud services that combine wireless networks with an agile, virtualized and software-defined edge cloud. In turn, 5G's growth is driving the need for such approaches as edge computing architectures, which place compute, storage and connectivity close to the data sources, either near or at the access network edge.
Unlike prior generations of wireless technology, 5G relies on strong, distributed cloud foundations of network and compute to power new market growth. Low latency, high bandwidth, trusted computing and storage rank are all core benefits of edge computing solutions. As a result, edge computing enabled with 5G can open up vast opportunities for application developers in manufacturing, gaming, automotive and other industries.
Service providers can deploy edge computing to enable specific services, applications and use cases. For this reason, edge architectures must be redesigned to meet the stringent SLAs (Service Level Agreements) of emerging applications, detect problems early and prevent service outages. Indeed, the combination of 5G and the Internet of Things (IoT) will foster new applications that need connectivity not just between people, but also between things.
Edge computing, with its new reference design, will also tap into embedded machine learning systems and artificial intelligence back-end modules to empower network intelligence and boost service agility and deployment.
Open source technologies and open white-box network elements will provide key software and hardware components for these reference designs. AI/ML can also play a significant role in improving network operations, especially at the network edge, and create new service opportunities.
Key takeaways from this webinar will include: