According to technology intelligence firm ABI Research, a sound distributed computing and artificial intelligence (AI) strategy will underpin successful 6G commercial deployment and enterprise use-case enablement.
“End-users in the 6G-era will not be concerned about merely connecting devices and creating data, but instead, they will want to extract valuable information from this data to make real-time operational decisions. Enterprise network expectation progression will mean that with the 6G rollout, the role of distributed computing is likely to change drastically,” said Reece Hayden, distributed and edge computing analyst at ABI Research.
“6G networks will need to be deployed across distributed computing domains with integrated edge AI resources to provide effective services for enterprise applications.”
The shift toward 6G will lead to greater convergence of technologies and a more prominent role for distributed computing integrated with edge AI. Three core 6G expectations will lead to this growth in distributed intelligence: technology, commercialization, and society:
- Technology: 6G is expected to be built in the sub-terahertz spectrum, meaning that deployment will be denser, while higher speeds will mean more data. Both of these factors mean the network will need to be built on top of a cloud-native, highly disaggregated, agile, distributed computing architecture that can intelligently scale to meet real-time deployment requirements while supporting revolutionary enterprise use cases.
- Commercialization: use-case enablement, data value extraction, and end-to-end network service expectations will mean that best-effort service level agreements (SLAs) are no longer acceptable. Instead, distributed intelligence resources will be required to provide real-time data computation and value extraction support, achieve guaranteed SLAs, and support telco network monetization through ubiquitous network slice deployment.
- Society: 6G is expected to drive sustainability and eliminate the digital divide. Distributed computing integration will aid data localization, limit backhauling, lower network power consumption, and put social value at the forefront.
But achieving the necessary integration of distributed computing and AI will not be simple, Hayden said. “Market standardization through increased cooperation and openness will be essential to overcoming the knowledge gaps and investment costs that could trouble telco-led technological convergence.”
“Although it remains early in the 6G development process, and often early expectations are far too bullish, meeting even some of the astronomical expectations for 6G networks will require a mature distributed intelligence strategy that fully leverages the network edge, telco cloud, and that deeply integrates intelligence within network deployment and enterprise services,” Hayden concluded.
