Scherrer SWu C.-YChiang Y.-HRothenberger BAsoni D.ESateesan AVliegen JMentens NPerrig A.HSU-CHUN HSIAO2022-04-252022-04-25202110609857https://www.scopus.com/inward/record.uri?eid=2-s2.0-85121591481&doi=10.1109%2fSRDS53918.2021.00034&partnerID=40&md5=7c8100872ddba5ecee29d74bc7833a8fhttps://scholars.lib.ntu.edu.tw/handle/123456789/607412Current probabilistic flow-size monitoring can only detect heavy hitters (e.g., flows utilizing 10 times their permitted bandwidth), but cannot detect smaller overuse (e.g., flows utilizing 50-100 % more than their permitted bandwidth). Thus, these systems lack accuracy in the challenging environment of high-Throughput packet processing, where fast-memory resources are scarce. Nevertheless, many applications rely on accurate flow-size estimation, e.g., for network monitoring, anomaly detection and Quality of Service. We design, analyze, implement, and evaluate LOFT, a new approach for efficiently detecting overuse flows that achieves dramatically better properties than prior work. LOFT can detect 1.50x overuse flows in one second, whereas prior approaches can only reliably detect flows that overuse their allocation by at least 3x. We demonstrate LOFT's suitability for high-speed packet processing with implementations in the DPDK framework and on an FPGA. ? 2021 IEEE.flow monitoringnetwork monitoringQuality of ServicesketchingAnomaly detectionBandwidth'currentFlow monitoringFlow sizesFlow tracersLow ratesNetwork MonitoringProbabilisticsQuality-of-serviceScalable algorithmsSketchingsQuality of serviceconference paper10.1109/SRDS53918.2021.000342-s2.0-85121591481