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To rigorously evaluate BRIGHT, we established a comprehensive experimental setup and defined clear evaluation metrics. We used the well-known GEANT backbone topology, which consists of 23 nodes and 74 links, simulating a realistic wide-area network environment. Our traffic model included 100 active flows, categorized into elephant and mouse flows, with both stationary and bursty traffic scenarios to test adaptability. We compare BRIGHT against three state-of-the-art baselines: LCM, AdaptMon, and OpenTM, ensuring a fair comparison against existing adaptive and low-cost monitoring solutions. Our evaluation focuses on four key metrics. First, we measure the monitoring overhead, specifically the number of OpenFlow messages per slot, as this directly impacts control-plane capacity. Second, we look at the effective link utilization, which quantifies how much link capacity is preserved for actual data traffic versus monitoring traffic. Third, we track the control-plane latency, which indicates the controllers responsiveness under load. Finally, and most importantly, we measure the accuracy of the estimated traffic matrix using the Root Mean Square Error, or RMSE. This ensures that our efficiency gains do not compromise the quality of the measurement data. This setup allows us to demonstrate that BRIGHT provides superior efficiency and adaptability without sacrificing accuracy. Lets look at the results under stationary traffic conditions.
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IEEE/ICACT20260358 Slide.15
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