Building Smart and Green Telecom Infrastructure using AI and Data

source: Total Telecom green summit

During last year industry has witnessed Telco’s increased spend and maturity in Cloud and Automation Platforms . During Pandemic it is proven that Digital and Cloud is the answer our customers require to design , build and Operate Future Telecom Networks .

The Second key Pillar forcing Telecom industry towards Autonomous networks is to deliver business outcomes while doing business responsibly .

Getting Business outcomes and doing a sustainable business that supports Green Vision has been a not related discussion in Telecom Industry

But now infusion of Data and Cloud is really enabling it , it is expected that we as industry can cutdown at least 50% of Power emissions in coming decade but how it will become possible . According to Pareto’s law the last 20% will be most difficult .

This is where my team main focus has been to build robust AI and Automation use cases that are intelligent enough and that solves broader issues . Today the biggest focus for ML/AI for Telco’s that can really put them lead such outcomes are

1. Smart Capacity management
2. O&M of networks that reduces emissions and improves availability
3. Service assurance based on data

The biggest Challenge in Transformation is Fragmentation

The biggest bottleneck is making such outcomes is related to data . Intricately “Data” is both the problem and the Solution because of so many sources of truth and different ingestion mechanisms . Do check details on #Dell Streaming data platforms and how we are solving this problem

https://www.delltechnologies.com/en-au/storage/streaming-data-platform.htm

Today under the umbrella of Anuket , 3GPP , TMF and ITU are all collaborating to come a validated and composite solution to deliver those use cases . So in a nutshell it is vital to build a holistic and unified view to deliver data driven AI use cases

Scope and Scale of Intelligent automation

The biggest bottleneck is coming from the fact that in real world Telco Apps can never be fully cloud native , at some level both the state and resiliency requirements and App requirements has to be kept and to come with intelligent work load driven decisions . The decade long journey of Telecom Transformation has revealed that just building everything as a code and expecting it to work and Telco’s can rollback their NOC sizes simply not works .

This is where intelligence from layers above the Orchestration and SDN will be of help like google does in the Internet era .

The second biggest issue is in the Scalable Telco solutions itself , it is proven that Telco’s face unique challenges as they move from hundred’s to thousand of nodes . So imagine running AI for heterogenous environments each coming with different outcomes can never deliver power and scale Telco’s need in the new era .

Telco grade AIOPS models

It is true that with 5G and Business digital transformation the industry really want to ramp up to build an improved user experience and unified model to expand portfolio towards vertical markets as well , this is only possible if we can have a coordinated system , workflow management and data sharing and exposure with strict TSR security measures . Similarly this model should cover full LCM including FCAPS model .

Building Intelligent Telco’s

Although using AI and ML is an exciting ambition for a Telco still the bottom line is how to build these platforms on top of NFVI and Existing Orchestration and Automation frameworks . In other words really business case to build an intelligent networks starts with using Data and ML to automate the entire network . Although in this aspect the scope can extend not just to service domain but also to business domains i.e automate business process including event correlation , anomaly and RCA

Building a Unified AI Platform

Although this intention or target is clear however in context of networks this is complex as we need to solve challenge of data security , regulation as well as what it really means to do the certification of an AI platform because focus should be given that allow this layer to be built from solution from many vendors so a loose coupling with more focus on Network service and AI algorithms is a key to build this platform

Instead of focusing on network element certification focus of AI platform is service level compatibility , data models and AI algorithms

However lack of unified standard specially on trusted data normalization , sharing and exposure is certainly forcing operators to adopt a Be-Spoke solutions to build AI platforms and that itself is a big impediment to wide scale adoption of AI and ML in the Networks

To move forward more close collaboration between different standard bodies and governance by more Telco centric organization like TMF is the answer with immediate focus to be given to Data standardization , labs integration and to enable shared data sets and algorithms to evolve and support wide deployments of ML and AI in Telecom Networks

Latest Industry progress and standardization

Although this is the early time of AI platforms standardization still we need to aggregate the progress between different bodies lest we can only expect the plethora of silo solutions each with a different specifications

• ONAP as baseline of automation platform has components like DCAE and AI engine that makes sense to make it the defacto baseline standard
• Anuket is the Cloud Infrastructure reference and it has recently launched a new project “Thoth” to look in to AI network standardization
• ETSI ZSM is E2E automation platform across full LCM of a Telecom network and certainly an important direction
• ETSI ENI or enhanced network intelligence is another body that closely defines AI specifications in the context of Telecom
• TMF as a broader Telecom body is defining architectures including ODA and AIOPS that really breaks down on how a Telco can take a phased approach to build these platforms

Above all early involvement and support from Telecom operators and partners is very important to realize this goal . I hope in this year we will see more success and standardization on these initiatives so lets work together and stay tuned .

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