Abstract

Urban broadband networks are crucial for communication, video streaming, and other digital services. However, in today's world, where high-speed connections are a necessity, studying network reliability, in particular, packet loss, has become vital. This urban broadband packet loss is the focus of this measurement-based study. Using urban monitoring probes, we gather packet data from multiple access networks, including fiber, DSL, and wireless broadband. Our goal is to determine the location and time packet loss occurs, its dependence on network traffic, and its response to varying time-of-day conditions. To quantify the loss burst and the distribution burst, a statistical modeling technique is used. We study the effects of packet loss on end-user services like VoIP and video streaming and thus calculate the practical Quality of Experience (QoE). We also propose a classifier for loss patterns in networks, which draws temporal feature vectors and uses supervised learning for validation. Our analysis shows that the majority of packet losses are bursty and linked to certain congested times. This research can help improve construction planning, resource distribution, and flexible network system algorithms.