TY - GEN
T1 - A faster and more efficient q-MAX algorithm
AU - Basat, Ran Ben
AU - Einziger, Gil
AU - Tayh, Bilal
N1 - Publisher Copyright:
© 2020 ACM.
PY - 2020/11/23
Y1 - 2020/11/23
N2 - The q-MAX problem, which seeks to find the q largest elements in a data stream, has numerous networking applications including sketches, network-wide heavy hitters, and others. In this poster, we propose an improvement to the q-MAX algorithm [5] that leverages sampling to accelerate the computation. Despite being randomized, our algorithm never fails (i.e., it is a Las Vegas algorithm) and runs up to 62% faster when evaluated on real packet traces and tasks. Moreover, on a real networking application and workload, our algorithm provides an 11-53% higher throughput.
AB - The q-MAX problem, which seeks to find the q largest elements in a data stream, has numerous networking applications including sketches, network-wide heavy hitters, and others. In this poster, we propose an improvement to the q-MAX algorithm [5] that leverages sampling to accelerate the computation. Despite being randomized, our algorithm never fails (i.e., it is a Las Vegas algorithm) and runs up to 62% faster when evaluated on real packet traces and tasks. Moreover, on a real networking application and workload, our algorithm provides an 11-53% higher throughput.
KW - algorithms
KW - data structures
KW - measurement
KW - monitoring
UR - http://www.scopus.com/inward/record.url?scp=85097590981&partnerID=8YFLogxK
U2 - 10.1145/3386367.3431671
DO - 10.1145/3386367.3431671
M3 - Conference contribution
AN - SCOPUS:85097590981
T3 - CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies
SP - 538
EP - 539
BT - CoNEXT 2020 - Proceedings of the 16th International Conference on Emerging Networking EXperiments and Technologies
PB - Association for Computing Machinery, Inc
T2 - 16th ACM Conference on Emerging Networking Experiment and Technologies, CoNEXT 2020
Y2 - 1 December 2020 through 4 December 2020
ER -