Multi-Access Edge Clouds, or MECs (often referred to as edge clouds or edge computing) represent a shift in cloud computing and networking, as they entail the strategic deployment of cloud resources at the periphery of the network (and in close proximity to where data is generated and consumed). The central goal of MECs is to reduce latency, enabling real-time or near-real-time processing for applications like AR, autonomous vehicles and industrial automation.
MECs are adaptable and can support various access networks, including 4G, 5G, Wi-Fi and fixed-line connections, making them versatile and capable of smooth traffic management. Their distributed architecture offers scalability and redundancy, while customized, application-specific services can be deployed at the edge.
To enable fully automated deployment of network and application workloads in MECs, FusionLayer announced a new solution blueprint for automating network instantiation and management processes in the edge clouds in collaboration with Nearby Computing.
FusionLayer is a company that provides patented Network Source (News - Alert) of Truth and IP addressing solutions that lay out the automation bedrock for the network functions, intelligent devices and business applications that connect through the next-generation edge clouds. Their solutions offer unparalleled visibility, scalability, and continuity across private data centers, public clouds and emerging multi-access edge clouds.
Nearby Computing is a Barcelona-based provider of edge computing services. They offer a platform for setting up, managing and automating hybrid, heterogeneous, and distributed IT systems, networks, applications, as well as defining and executing complex value-added end-to-end services.
So, how will the blueprint work?
With the increasing integration of AI into everyday life, the Information and Communications Technology sector has delved into exploring the future infrastructure essential for accommodating forthcoming AI-powered applications. This exploration has laid the groundwork for a novel cloud computing approach termed "edge cloud computing," designed to shift applications from public clouds to localized data centers. Still, security is a critical concern, necessitating robust measures to safeguard data and infrastructure
This innovative framework between FusionLayer and Nearby Computing is anticipated to enhance the security and responsiveness of AI-driven solutions, marking a departure from conventional cloud setups.
“By combining the patented Network Source of Truth technology by FusionLayer with Nearby Computing’s innovative orchestrator for network automation, customers are able to automate network instantiation and also many other management tasks,” said Juha Holkkola, the Co-Founder and CEO of FusionLayer. “This opens new ways to monetize the network infrastructure.”
MECs are also particularly influential within the 5G network context, harnessing 5G's high-speed, low-latency capabilities to offer a diverse range of services, spanning from IoT to AR experiences. By relocating cloud resources to the network's edge, MECs are poised to revolutionize digital technology engagement, potentially driving innovation through diverse and immersive applications.
In the pursuit of realizing the potential of MECs, the telecom industry has heavily invested in emerging technologies like 5G. Yet, these investments have not yielded substantial returns. To attract new investments in the edge cloud computing infrastructure required for AI-enabled applications, the industry is introducing remotely programmable network services that expose network functions through APIs, fostering new NaaS business models.
FusionLayer and Nearby Computing's collaborative blueprint further extends this opportunity.
“The network source of truth is an essential component for running full process automation for virtualized networks,” said Josep Martí, CEO of Nearby Computing.
When all said and done, FusionLayer and Nearby Computing's visionary blueprint, embracing automation and innovation, makes the network infrastructure more agile, efficient and ready for the AI-powered future.
Edited by Alex Passett