One Sketch to Rule Them All: Rethinking Network Flow Monitoring with UnivMon
Zaoxing Liu,Antonis Manousis,Gregory Vorsanger,Vyas Sekar,Vladimir Braverman +4 more
- pp 101-114
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TLDR
UnivMon is presented, a framework for flow monitoring which leverages recent theoretical advances and demonstrates that it is possible to achieve both generality and high accuracy, and evaluated using a range of trace-driven evaluations to show that it offers comparable (and sometimes better) accuracy relative to custom sketching solutions.Abstract:
Network management requires accurate estimates of metrics for traffic engineering (e.g., heavy hitters), anomaly detection (e.g., entropy of source addresses), and security (e.g., DDoS detection). Obtaining accurate estimates given router CPU and memory constraints is a challenging problem. Existing approaches fall in one of two undesirable extremes: (1) low fidelity general-purpose approaches such as sampling, or (2) high fidelity but complex algorithms customized to specific application-level metrics. Ideally, a solution should be both general (i.e., supports many applications) and provide accuracy comparable to custom algorithms. This paper presents UnivMon, a framework for flow monitoring which leverages recent theoretical advances and demonstrates that it is possible to achieve both generality and high accuracy. UnivMon uses an application-agnostic data plane monitoring primitive; different (and possibly unforeseen) estimation algorithms run in the control plane, and use the statistics from the data plane to compute application-level metrics. We present a proof-of-concept implementation of UnivMon using P4 and develop simple coordination techniques to provide a ``one-big-switch'' abstraction for network-wide monitoring. We evaluate the effectiveness of UnivMon using a range of trace-driven evaluations and show that it offers comparable (and sometimes better) accuracy relative to custom sketching solutions.read more
Citations
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Proceedings ArticleDOI
Elastic sketch: adaptive and fast network-wide measurements
Tong Yang,Jie Jiang,Peng Liu,Qun Huang,Junzhi Gong,Yang Zhou,Rui Miao,Xiaoming Li,Steve Uhlig +8 more
TL;DR: The Elastic sketch is proposed, which is adaptive to currently traffic characteristics, generic to measurement tasks and platforms, and implemented on six platforms to process typical measurement tasks.
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Heavy-Hitter Detection Entirely in the Data Plane
Vibhaalakshmi Sivaraman,Srinivas Narayana,Ori Rottenstreich,S. Muthukrishnan,Jennifer Rexford +4 more
TL;DR: This work proposes HashPipe, a heavy hitter detection algorithm using emerging programmable data planes which implements a pipeline of hash tables which retain counters for heavy flows while evicting lighter flows over time.
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Language-Directed Hardware Design for Network Performance Monitoring
Srinivas Narayana,Anirudh Sivaraman,Vikram Nathan,Prateesh Goyal,Venkat Arun,Mohammad Alizadeh,Vimalkumar Jeyakumar,Changhoon Kim +7 more
TL;DR: A performance query language, Marple, modeled on familiar functional constructs like map, filter, groupby, and zip is presented, backed by a new programmable key-value store primitive on switch hardware.
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Sonata: query-driven streaming network telemetry
TL;DR: Sonata provides a declarative interface to express queries for a wide range of common telemetry tasks and reduces the workload for the stream processor by as much as seven orders of magnitude compared to existing telemetry systems.
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SketchVisor: Robust Network Measurement for Software Packet Processing
TL;DR: SketchVisor augments sketch-based measurement in the data plane with a fast path, which is activated under high traffic load to provide high-performance local measurement with slight accuracy degradations and recovers accurate network-wide measurement results via compressive sensing.
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