A Scalable Telemetry Framework for Zero Touch Optical Network Management

The interest about Zero Touch Network and Service Management (ZSM) is rapidly emerging. As defined by ETSI, the ZSM architecture is based on a closed-loop/feedback control of the network and the services. Such closed-loop control can be based on the Boyd’s Observe Orient Decide and Act (OODA) loop that matches some specific management functions such as Data Collection, Data Analytics, Intelligence, Orchestration and Control. An efficient implementation of such control loop allows the network to timely adapt to changes and maintain the required quality of service.Many solutions for collecting network parameters (i.e., implementing ZSM data collection) are proposed that fall under the broad umbrella of network telemetry. An example is the Google gRPC, that represented one of the first solutions to provide a framework for data collection. Since then, the number of available frameworks is proliferating. In this paper we propose the utilisation of Apache Kafka as a framework for collecting optical network parameters. Then, the paper goes beyond that by proposing and showing how Apache Kafka can be effective for supporting data exchange and management of whole ZSM closed-loop.Experimental evaluation results show that, even when a large number of data are collected, the solution is scalable and the time to disseminate the parameter values is short. Indeed, the difference between the reception time and the generation time of data is, on average, 40-50ms when about four thousand messages are generated.

[1]  Shoukei Kobayashi,et al.  Field Demonstration of Real-Time Optical Network Diagnosis using Deep Neural Network and Telemetry , 2019, 2019 Optical Fiber Communications Conference and Exhibition (OFC).

[2]  Tarik Taleb,et al.  AI-Driven Zero Touch Network and Service Management in 5G and Beyond: Challenges and Research Directions , 2020, IEEE Network.

[3]  Haoyu Song,et al.  Network Telemetry Framework , 2019, RFC.

[4]  Marc Ruiz,et al.  Autonomic disaggregated multilayer networking , 2018, IEEE/OSA Journal of Optical Communications and Networking.

[5]  Koteswararao Kondepu,et al.  Orchestrating Edge- and Cloud-based Predictive Analytics Services , 2020, 2020 European Conference on Networks and Communications (EuCNC).

[6]  E. Riccardi,et al.  Fully Disaggregated ROADM White Box with NETCONF/YANG Control, Telemetry, and Machine Learning-based Monitoring , 2018, 2018 Optical Fiber Communications Conference and Exposition (OFC).

[7]  Nei Kato,et al.  State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems , 2017, IEEE Communications Surveys & Tutorials.

[8]  Adlen Ksentini,et al.  Improving Traffic Forecasting for 5G Core Network Scalability: A Machine Learning Approach , 2018, IEEE Network.

[9]  Raul Muñoz,et al.  Scalable telemetry and network autonomics in ACTN SDN controller hierarchy , 2017, 2017 19th International Conference on Transparent Optical Networks (ICTON).

[10]  Piero Castoldi,et al.  Network Telemetry Streaming Services in SDN-Based Disaggregated Optical Networks , 2018, Journal of Lightwave Technology.

[11]  Loukas Paraschis,et al.  High Performance Streaming Telemetry in Optical Transport Networks , 2018, 2018 Optical Fiber Communications Conference and Exposition (OFC).

[12]  Stream Processing for Optical Network Monitoring with Streaming Telemetry and Video Analytics , 2020, 2020 European Conference on Optical Communications (ECOC).

[13]  A. Sgambelluri,et al.  Exploiting Telemetry in Multi-Layer Networks , 2020, 2020 22nd International Conference on Transparent Optical Networks (ICTON).

[14]  Magda Osman,et al.  Control Systems Engineering , 2010 .

[15]  Ramon Casellas,et al.  Building Autonomic Optical Whitebox-Based Networks , 2018, Journal of Lightwave Technology.

[16]  Deval Bhamare,et al.  Programmable Event Detection for In-Band Network Telemetry , 2019, 2019 IEEE 8th International Conference on Cloud Networking (CloudNet).

[17]  Marco Gramaglia,et al.  Mobile traffic forecasting for maximizing 5G network slicing resource utilization , 2017, IEEE INFOCOM 2017 - IEEE Conference on Computer Communications.

[18]  Filippo Cugini,et al.  OpenConfig and OpenROADM Automation of Operational Modes in Disaggregated Optical Networks , 2020, IEEE Access.

[19]  Loukas Paraschis,et al.  Demonstration of Extensible Threshold-Based Streaming Telemetry for Open DWDM Analytics and Verification , 2020, 2020 Optical Fiber Communications Conference and Exhibition (OFC).

[20]  Shu Namiki,et al.  Submilisecond Control/Monitoring of Disaggregated Optical Node through a Direct Memory Access based Architecture , 2019, 2019 Optical Fiber Communications Conference and Exhibition (OFC).

[21]  Optimized, Automated, and Protective: An Operator’s View on Future Networks , 2021, IEEE Transactions on Network and Service Management.

[22]  Biswanath Mukherjee,et al.  Emergency OPM Recreation and Telemetry for Disaster Recovery in Optical Networks , 2020, Journal of Lightwave Technology.

[23]  Marc Ruiz,et al.  An Architecture to Support Autonomic Slice Networking , 2018, Journal of Lightwave Technology.

[24]  A. Campanella,et al.  Intent Based Network Operations , 2019, 2019 Optical Fiber Communications Conference and Exhibition (OFC).

[25]  Jan Kundrat,et al.  Opening up ROADMs: a filterless add/drop module for coherent-detection signals , 2020, IEEE/OSA Journal of Optical Communications and Networking.