The Challenge of Zero Touch and Explainable AI




Zero touch, closed loop, 5G, analytics, machine learning, explainable AI


With ever increasing complexity and dynamicity in digital service provider networks, especially with the emergence of 5G, operators seek more automation to reduce the cost of operations, time to service and revenue of new and innovative services, and increase the efficiency of resource utilization, Complex algorithms leveraging ML (machine learning) are introduced, often with the need for frequent training as the networks evolve. Inference is then applied either in the core directly, or in the management stack to trigger actions and configuration changes automatically. This is the essence of Zero Touch. The challenge that analysts are often faced with is to trace back from the inference or prediction to the original events or symptoms that led to the triggered action, which ML model version or pipeline was used. This paper describes the challenges faced by analysts and provides some solutions.


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Author Biographies

Biswadeb Dutta, HPE, Palo Alto, United States

Biswadeb Dutta is a lead architect and member of the product engineering organization of HPE’s Communications Technology Group. Biswadeb leads the architecture and development of HPE’s OSS assurance portfolio. Among several of his responsibilities, Biswadeb focuses on the application of AI and ML to address problems arising in the assurance space for telecommunications networks and digital service provider operations. Biswadeb has worked with several of the largest digital service providers across the globe and assisted them in addressing their operations challenges.

Andreas Krichel, HPE, Palo Alto, United States

Andreas Krichel Andreas Krichel is Distinguished Technologist in the Portfolio Strategy management team for HPE’s Communications Technology Group. His focus is on the 5G E2E automation across the different product families. Andreas led the architecture for HPE’s flagship orchestration product Service Director. Today Andreas works active in standards such as ETSI ZSM and is lead technologist for various customer engagements around zero-touch management and 5G.

Marie-Paule Odini, HPE, Palo Alto, United States

Marie-Paule Odini is Distinguished Technologist in HPE Telecom Division focused on customer innovation and emerging trends including NFV, SDN, IoT, AI, 5G and 6G. Active in industry forums and standard organization. She is Chair of GreenG and held key positions such as ETSI NFV Vice Chair, IEEE SDN Chair, Editorial board member, 5G Americas key contributor, co-chair of TIP E2E network slicing project and Next Gen Alliance Steering board member. Prior to HPE she worked in France Telecom/Orange labs.


Gartner AIOps –

XAI – Darpa –

Europe explainable AI –

ETSI ZSM002 – Zero-touch network and Service Management (ZSM); Reference Architecture.

ETSI ZSM005 – Zero-touch network and Service Management (ZSM); Means of Automation.

3GPP TS 28.533 5G Management and orchestration; Architecture framework.

3GPP TS 29.520 5G System; Network Data Analytics Services.

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HPE 5G Orchestration and Automation Toward Zero-touch Service Management.

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ITU-T Y.3172: Architectural framework for machine learning in future network including IMT-2020.

ITU-T Y.3174: Machine learning marketplace integration in future networks including IMT-2020.

ITU-T Y.3176: Machine learning marketplace integration in future networks including IMT-2020.

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3GPP TS 23.501 System architecture for the 5G System (5GS).






Special Issue on Zero-touch Network and Service Automation (ZSM)