--Finding hierarchical heavy hitters (HHHs) (i.e., hierarchical aggregates with exceptionally huge amounts of traffic) is critical to network management, yet it is often challenged by the requirements of fast packet processing, real-time and accurate detection, as well as resource efficiency. Existing HHH detection schemes either incur expensive packet updates for multiple aggregation levels in the IP address hierarchy, or need to process sufficient packets to converge to the required detection accuracy. We present MVPipe, an invertible sketch that achieves both lightweight updates and fast convergence in HHH detection. MVPipe builds on the skewness property of IP traffic to process packets via a pipeline of majority voting executions, such that most packets can be updated for only one or few aggregation levels in the IP address hierarchy. We show how MVPipe can be feasibly deployed in P4-based programmable switches subject to limited switch resources. We also theoretically analyze the accuracy and coverage properties of MVPipe. Evaluation with real-world Internet traces shows that MVPipe achieves high accuracy, high throughput, and fast convergence compared to six state-of-the-art HHH detection schemes. It also incurs low resource overhead in the Barefoot Tofino switch deployment.
[1]
Martín Casado,et al.
The Design and Implementation of Open vSwitch
,
2015,
NSDI.
[2]
Divyakant Agrawal,et al.
Efficient Computation of Frequent and Top-k Elements in Data Streams
,
2005,
ICDT.
[3]
Thomas Steinke,et al.
Hierarchical Heavy Hitters with the Space Saving Algorithm
,
2011,
ALENEX.
[4]
Anja Feldmann,et al.
Leveraging Zipf's law for traffic offloading
,
2012,
CCRV.
[5]
Walter Willinger,et al.
Sonata: query-driven streaming network telemetry
,
2018,
SIGCOMM.
[6]
Richard M. Karp,et al.
A simple algorithm for finding frequent elements in streams and bags
,
2003,
TODS.
[7]
Ori Rottenstreich,et al.
Efficient Measurement on Programmable Switches Using Probabilistic Recirculation
,
2018,
2018 IEEE 26th International Conference on Network Protocols (ICNP).
[8]
Anirudh Sivaraman,et al.
Language-Directed Hardware Design for Network Performance Monitoring
,
2017,
SIGCOMM.