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ETSI embraces AI to address rising network complexity

The growing complexity of networks is forcing telecom operators and systems vendors to turn to machine intelligence for help. It has led the European Telecommunications Standards Institute, ETSI, to set up an industry specification group to define how artificial intelligence (AI) can be applied to networking.

 “With the advent of network functions virtualisation and software-defined networking, we can see the eventuality that network management is going to get very much more complicated,” says Ray Forbes, convenor of the ETSI Industry Specification Group, Experimental Network Intelligence (ISG-ENI).

Source: ETSI

The AI will not just help with network management, he says, but also with the introduction of services and the more efficient use of network resources.

Visibility of events at many locations in the network will be needed with the deployment of network functions virtualisation (NFV), says Forbes. In current networks, a large switch may serve hundreds of thousands of users but with NFV, virtual network functions will be at many locations. The ETSI group will look at how AI can be used to manage and control this distributed deployment of virtual network functions, says Forbes. 

The group’s work has started by inviting interested parties to bring and discuss use cases from which a set of requirements will be generated. In parallel, the group is looking at AI techniques.

The aim is to use computing to derive data from across the network. The data will be analysed, and by having 'context awareness', the machine intelligence will compute various scenarios before presenting the most promising ones for consideration by the network management team. “The process is collecting data, analysing it, testing out various scenarios and then advising people on what would happen in the better scenarios,” says Forbes.


With the advent of NFV and SDN, we can see the eventuality that network management is going to get very much more complicated


ETSI's goal is to make it easier for operators to deploy services quickly, reroute around networking faults, and make better use of networking resources. “In very large cities like Shanghai and Tokyo, where there are populations of 25 million, there is a need for this,” says Forbes. “In London, with about 12 million people, there is still a need but not quite so quickly.”   

Operators and system vendors have some understanding of AI but there is a learning curve in bringing more and more AI experts on board, says Forbes: "Hence, we are trying to involve various universities in the research project."


Project schedule

The ISG-ENI's initial document work will be followed by defining the architecture and specifying the parameters needed to measure the network and the 'intelligence' of the scenarios.

“ETSI has a two-year project with the possibility of an extension,” says Forbes, with AI deployed in networks as early as 2019.  

Forbes says open-source software to add AI to networks could be available as soon as 2018. Such open-source software will be developed by operators and systems vendors rather than ETSI.

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