Data Collection, Interpretation Methodologies, and Challenges for Proactive Network Maintenance (2023)

By James Medlock, Akleza, Inc.; Ron Hranac, SCTE; Allen Maharaj, Rogers; Alexander Podarevsky, Promptlink Communications; Jason Rupe, CableLabs; Foad Towfiq, Promptlink Communications; Brady Volpe, Volpe Firm

Proactive network maintenance (PNM) measurements have been a part of DOCSIS® specifications for over a decade now, but data collection and interpretation are still a challenge for many, both vendors and operators. The DOCSIS specifications define how to request measurement data and the format within which it is to be returned but stop short of properly outlining their use. Furthermore, vendor implementations vary, and newer DOCSIS architectures have added their own challenges to this problem. As PNM tools evolve, we have learnt that our ability to gather the data can be impacted by the collection mechanism in ways we as an industry are unable to qualify in documentation without defining use cases. The PNM Working Group (PNM-WG) at CableLabs, in conjunction with SCTE Network Operations Subcommittee Working Group 7 (NOS WG7) on PNM, continues to evolve the recommended best practices for this data to assist with troubleshooting network issues. As the network ecosystems are further investigated, gaps are identified that create additional concerns to be addressed. One such gap is that all the information available does not guarantee network equipment behaves as designed when faults occur. Some uses for this data require more than has been specified or described. To help the industry take full advantage of PNM data, the PNM-WG at CableLabs continuously develops use cases, guiding interested parties in the capture and utilization of PNM data to the benefit of both vendors and operators alike. In this paper we review the available data collection methods and discuss several PNM use cases to help the reader understand how PNM data can be used in the real world, identify challenges based on current implementations, and propose improvements to the collection methods and PNM data where needed.

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