Predictive Framework for Enhanced Wireline Network Reliability (2024)

By Madiha Sahar, Rogers Telecommunications; Ray Stevens, Rogers Telecommunications; Jenny Panman, Rogers Telecommunications; Vikram Karwal, Rogers Telecommunications; Anna Korchatov, Rogers Telecommunications; Peter Theodorakidis, Rogers Telecommunications; Davy Ma, Rogers Telecommunications

In today’s sophisticated wireline network infrastructures, the Cable Modem Termination System (CMTS) interfaces with customer homes through an intricate array of branching connections, establishing distinct pathways for each subscriber. This setup not only facilitates individualized connections but also constitutes a comprehensive map of the access network. This map delineates key network elements including ports, media access control (MAC) domains, and critical components such as amplifiers and splitters, all of which play essential roles in managing the link between the gateway modem and the CMTS.

At the heart of this connectivity is the node, a pivotal aggregation point strategically located based on geographic considerations. Each node typically services a varying number of devices, making it an optimal point to measure quality of service (QoS) of the access network.

QoS is a critical measure used to evaluate and ensure the reliability and efficiency of these network connections. It encompasses various metrics such as network latency, availability, bandwidth, jitter, and packet loss, which collectively determine the network’s ability to deliver a consistent and high-quality user experience. Measuring QoS at the node level is crucial for identifying and addressing area-specific issues within the access network. By focusing on nodes, network operators can differentiate between widespread, location-specific problems and individual customer issues.

This targeted measurement and analysis not only help maintain a responsive, reliable, and accessible network for all users but also assist service technicians in pinpointing and isolating root causes of network problems. By identifying issues at the node level, technicians can more effectively plan and execute targeted interventions, addressing network-wide problems more efficiently and minimizing disruptions for individual customers

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