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When considering the role of open source software in addressing the challenges of Network AI it is important to understand the current landscape of projects and initiatives and how they came into existence. Several such initiatives have already laid down the ground work for build
5.1 Related Open Source Landscape
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building Network AI solutions, or are actively working on creating them. Building on these foundations, it is possible to envision what role open source software will play in unleashing the power of AI for the future generations of networks. Some of the required technologies required of Network AI are unique to the Networking industry, and will have to be addressed by the existing OSS projects on the landscape, or by creation of additional ones. Some of the other pieces of technology are more generic, and will come from the broad landscape of AI OSS. Here is a rough outline of the different layers of Networking AI and the source of the required technology:
5.1 Related Open Source Landscape
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- Network communities
Open Source Software (OSS) communities have been successfully building projects that provide the building blocks of networks for over decade now. OSS projects provide the underlying technology for all layers of the network, including the data/forwarding plane, control plane, management and orchestration. A vibrant ecosystem of contributing companies exists around these projects, consisting of organizations that realized the value in the principles OSS for networking:
- Shared effort to develop the foundation layers of the technology, freeing up more resources to develop the value-add layers
- A neutral platform for innovation where individuals and organizations can exchange ideas and come up with best of breed technology solutions
- An opportunity to demonstrate thought leadership and domain expertise
- A collaboration space where producers and consumers of technology can freely interact and create business opportunities
Many of the networking OSS projects are hosted by the Linux Foundation. Most of them are part of LF Networking, LF Connectivity and LF Broadband.
- AI communities
The same principles are now being applied to the shared development of Network AI technologies, where the open source community fosters innovation and stimulates business growth. AI innovation has been strongly propelled by OSS projects that were initiated following the same principles mentioned above. It is hard to imagine doing any modern AI development without heavily relying on OSS. OSS AI and ML projects range from anything between the framework for developing , Libraries and programming tools. Data scientists who develop domain specific models do not have to start from scratch, instead they can leverage OSS projects to jump start their work and focus on creation of innovation. It would be almost impossible to mention all the relevant OSS AI projects here as there are already so many of them, and the list keeps growing quickly. The Linux Foundation AI&Data provides a useful dynamic landscape here.
Successful development of AI models for use in Networking relies on the availability of data that could be shared under a common license. The Linux Foundation created the Community Data License Agreement (CDLA) for this purpose. Using this license, end users can share data and make it available for researches, who in turn develop the necessary models and applications that benefit the end users.
When it comes to the popular subject of LLMs, there is a lot of debating going on currently about what an "Open AI model" really means. While it is out of the scope of this paper to try and settle any of those debates, it is obvious that there is a clear need to create the definition of "open LLM". The sooner such definition is created and blessed by the industry, the faster innovation can happen.
- Integration blueprints
In recent years The Linux Foundation Networking launched a set of Open Source Networking "Super Blueprints" that outline architectures for common networking use cases and are built using OSS technology. Those blueprints consists of collections of OSS projects and commercial products, integrated together by the open source community and documented for free use by any interested party. Several of these blueprints started incorporating AI technologies and we expect that trend to accelerate, as existing blueprints inspire additional AI-driven solutions. One promising area is intent-based network automation. There is current work on blueprints that use NLP and LLM to translate user intent, expressed in natural spoken language to network requirements, and generate full network configuration based on those requirements. Such approach can significantly simplify existing network operation processes, and enable new services that can be directly consumed by the end users in an automated manner (known as Network-as-a-Service - NaaS)
- Verification programs
Experience with OSS in other domains shows that whenever there is an OSS technology that powers commercial products or offerings, there is a need to validate the products to make sure they are properly using the OSS technology and are ready to serve the end users in a predictable manner. Such validation/verification programs have existed for a while as part of OSS ecosystems. They are often created and maintained by the same OSS community that develops the OSS projects themselves. The Cloud Native Computing Foundation (CNCF) has a successful "Certified Kubernetes" program that helps vendors and end users ensure that Kubernetes distributions provide all the necessary APIs and functionality. A similar approach should be applied to any OSS Networking AI projects. End users should have a certain level of confidence, knowing that the OSS based AI Networking solution they use will behave as expected.
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5.2 Common Vision: intelligence plane for XG Ranny Haiby Muddasar Ahmed
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- l natural intent interaction
- l cognitive smart orchestration
- l real-time meta-network verification
- l built-in knowledge open loops
Ranny Haiby is this what your were thinking for this section:
In the dynamic realm of communication technologies, the fusion of artificial intelligence (AI) with networks promises to redefine connectivity, ushering in an era of unprecedented intelligence, efficiency, and adaptability. As we embark on the journey towards 6G and embrace the vision outlined by the International Telecommunication Union (ITU) for IMT-2030, it becomes clear that AI will play a pivotal role in reshaping network operations.
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