By Allen Maharaj, Rogers Communications; Jason Rupe, Cablelabs; Alexander Podarevsky, Promptlink Communications; Foad Towfiq, Promptlink Communications; Albert J Kim, Rogers Communications
DOCSIS® Proactive Network Maintenance (PNM) is crucial for cable operators to enhance network performance and reliability. By monitoring and analyzing data from network devices, PNM can detect issues early, improving service quality and subscriber satisfaction. Despite its benefits, PNM faces challenges that limit its effectiveness.
Developed over a decade ago, PNM reduces maintenance costs and service disruptions. It enables both proactive and efficient reactive repairs, enhancing performance measures and key performance indicators.
PNM data supports proactive repair planning, minimizing costs and customer impact, and streamlines reactive repairs by pinpointing faults. Additionally, PNM queries and tests provide insights for continuous improvement in service and network performance. As PNM evolves, its impact on network operations grows, ensuring its importance in cable network operations.
However, operators encounter challenges in implementing and expanding PNM operations. These include data overload, ineffective reporting structures, inefficient processes, and non-standard vendor implementations. Data overload complicates processing and analysis, obscuring actionable insights and hindering timely decision-making. Ineffective reporting structures make it difficult to optimize the network, while inefficient processes delay issue resolution. Non-standard vendor implementations cause interoperability issues.
This paper analyzes these challenges and their impact on network management, using real-world examples and case studies. It offers recommendations and solutions for optimization, helping operators enhance PNM effectiveness and improve network performance and subscriber experience. While noncompliance with PNM telemetry reporting standards is known, this paper focuses on managing the data once it is available. The PNM Working Group (PNM-WG) at CableLabs has been working to define PNM use cases, and this paper addresses how to utilize the data effectively once it is obtained, akin to determining once the dog catches the car, what does the dog do?