this article introduces the test design, sampling methods and analysis points based on the actual measurement of delay and packet loss in hong kong telecom's pccw computer room in a multi-line environment. the goal is to provide reproducible methodologies and actionable optimization suggestions to help operation and maintenance and engineering teams evaluate the real performance of the computer room under off-site backhaul and link redundancy conditions.
overview of testing environment and methods
the test was conducted in a pccw computer room where multiple ingress links and redundant routes coexisted, using three test methods: icmp, tcp handshake and udp traffic simulation. the test cycle covers peak and off-peak periods, using distributed probes and recording rtt, packet loss rate and jitter to ensure the representativeness and comparability of the data.
multi-line topology and traffic distribution strategy
multi-line topology includes three common methods: active and backup, load balancing and policy routing. the actual measurement focuses on the bandwidth utilization of each line, forwarding priority and the impact of bgp/ospf routing decisions on traffic distribution to evaluate service continuity and delay fluctuations when links are degraded or switched.
latency test results and trend interpretation
the latency test is based on rtt distribution and analyzes the average, median and 95th percentile. the results focus on the increase in latency in cross-border backhaul, link switching instants, and high concurrency situations. the routing path and queue length are combined to infer the source of latency and whether there are network issues such as buffer expansion.
jitter and short-term peak analysis
jitter analysis uses short-time window statistics and focuses on the impact of jitter frequency and amplitude on real-time services. short-term peaks are often related to congestion, route re-convergence, or equipment processing high load. combined with time series, it can be determined whether it is caused by periodic traffic or abnormal events.
packet loss rate test results and influencing factors
the packet loss rate test covers three types of indicators: icmp, tcp retransmission and udp packet loss, which reflect link quality and transport layer recovery capabilities respectively. factors affecting packet loss include link congestion, error frames, link switching, and equipment failure; combined with logs, it can be distinguished whether it is a link-level problem or an upper-layer scheduling policy.
route switching and backup link performance
evaluate the convergence time and packet loss/delay impact during route switching, and perform stress tests on active/standby switchover, bgp convergence, and ecmp scenarios. pay attention to handover trigger conditions, session persistence policies, and recovery capabilities under different loads to measure backup link availability.
performance bottleneck location and optimization suggestions
through delay distribution, packet loss period and traffic path intersection analysis, link congestion, device processing bottlenecks or policy configuration defects can be located. suggestions include properly configuring queue management, optimizing routing strategies, increasing monitoring granularity, and conducting regular stress testing to improve stability and observability.
continuous practice of monitoring and verification
it is recommended to establish an slo-oriented monitoring system that combines active detection and passive traffic sampling to continuously verify latency and packet loss indicators. regularly review test scripts and scenarios to simulate failover and traffic surges to ensure that indicator thresholds and alarm strategies are consistent with business needs.
summary and suggestions
based on the actual measurement of delay and packet loss in hong kong telecom's pccw computer room in a multi-line environment, it is recommended to make targeted improvements based on hierarchical testing, time period coverage and path visualization, combined with routing strategies and queue optimization. through continuous monitoring and regular retesting, link stability can be significantly improved and user-perceived network fluctuations can be reduced.

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