TY - GEN
T1 - Faster and More Accurate Measurement through Additive-Error Counters
AU - Basat, Ran Ben
AU - Einziger, Gil
AU - Mitzenmacher, Michael
AU - Vargaftik, Shay
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/7/1
Y1 - 2020/7/1
N2 - Counters are a fundamental building block for networking applications such as load balancing, traffic engineering, and intrusion detection, which require estimating flow sizes and identifying heavy hitter flows. Existing works suggest replacing counters with shorter multiplicative error estimators that improve the accuracy by fitting more of them within a given space. However, such estimators impose a computational overhead that degrades the measurement throughput. Instead, we propose additive error estimators, which are simpler, faster, and more accurate when used for network measurement. Our solution is rigorously analyzed and empirically evaluated against several other measurement algorithms on real Internet traces. For a given error target, we improve the speed of the uncompressed solutions by 5×-30×, and the space by up to 4×. Compared with existing state-of-the-art estimators, our solution is 9×-35× faster while being considerably more accurate.
AB - Counters are a fundamental building block for networking applications such as load balancing, traffic engineering, and intrusion detection, which require estimating flow sizes and identifying heavy hitter flows. Existing works suggest replacing counters with shorter multiplicative error estimators that improve the accuracy by fitting more of them within a given space. However, such estimators impose a computational overhead that degrades the measurement throughput. Instead, we propose additive error estimators, which are simpler, faster, and more accurate when used for network measurement. Our solution is rigorously analyzed and empirically evaluated against several other measurement algorithms on real Internet traces. For a given error target, we improve the speed of the uncompressed solutions by 5×-30×, and the space by up to 4×. Compared with existing state-of-the-art estimators, our solution is 9×-35× faster while being considerably more accurate.
UR - http://www.scopus.com/inward/record.url?scp=85090279346&partnerID=8YFLogxK
U2 - 10.1109/INFOCOM41043.2020.9155340
DO - 10.1109/INFOCOM41043.2020.9155340
M3 - Conference contribution
AN - SCOPUS:85090279346
T3 - Proceedings - IEEE INFOCOM
SP - 1251
EP - 1260
BT - INFOCOM 2020 - IEEE Conference on Computer Communications
PB - Institute of Electrical and Electronics Engineers
T2 - 38th IEEE Conference on Computer Communications, INFOCOM 2020
Y2 - 6 July 2020 through 9 July 2020
ER -