Detecting heavy flows in the SDN match and action model

Afek, Yehuda; Bremler-Barr, Anat; Feibish, Shir Landau; Schiff, Liron

doi:10.1016/j.comnet.2018.02.018

Cited by 56 publications

(28 citation statements)

References 13 publications

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“…DiffFlow [30] also uses packet sampling to perceive the existence of long flows in the network, but does not explore the sampling performance in detail. Other works include MircoTE [31], OpenSample [32], Sample&Pick [33], etc. These solutions focused on data center network load balancing, and did not have a good answer to how to obtain network long flow information.…”

Section: Samplingmentioning

confidence: 99%

Sonum: Software-Defined Synergetic Sampling Approach and Optimal Network Utilization Mechanism for Long Flow in a Data Center Network

Tan

Cheng

et al. 2019

Applied Sciences

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Long flow detection and load balancing are crucial techniques for data center running and management. However, both of them have been independently studied in previous studies. In this paper, we propose a complete solution called Sonum, which can complete long flow detection and scheduling at the same time. Sonum consists of a software-defined synergetic sampling approach and an optimal network utilization mechanism. Sonum detects long flows through consolidating and processing sampling information from multiple switches. Compared with the existing prime solution, the missed detection rate of Sonum is reduced by 2.3%–5.1%. After obtaining the long flow information, Sonum minimizes the potential packet loss rate as the optimization target and then translates load balancing into an optimization problem of arranging a minimum packet loss path for long flows. This paper also introduces a heuristic algorithm for solving this optimization problem. The experimental results show that Sonum outperforms ECMP and Hedera in terms of network throughput and flow completion time.

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Section: Samplingmentioning

confidence: 99%

Sonum: Software-Defined Synergetic Sampling Approach and Optimal Network Utilization Mechanism for Long Flow in a Data Center Network

Tan

Cheng

et al. 2019

Applied Sciences

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“…One solution to this problem is to keep track only the large/heavy flows. A large flow is a flow that includes more than a certain percentage of the packets during a given time interval [Afek et al 2018]. Studies have shown that the majority of flows tend to be short (mice flows) on high-speed links.…”

Section: Design Guidelinesmentioning

confidence: 99%

SFCMon: An Efficient and Scalable Monitoring System for Network Flows in SFC-enabled Domains

Bonfim¹,

Dias²,

Fernandes³

2019

Anais Do Workshop Pré-Ietf (WPIETF)

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A comprehensive monitoring system is essential to assist solutions for most of SFC problems. Therefore, in this work, we propose SFCMon, an efficient and scalable monitoring solution to keep track network flows in SFC environments. To achieve the desired goals, SFCMon works with a pipeline of probabilistic data structures to detect and store large flows as well as perflow counters. For evaluation purposes, based on the SFC reference architecture defined by RFC 7665, we implement a Proof-of-Concept (PoC) framework, which provides a P4-based SFC switch and Python-based SFC Controller. Presented initial experiments demonstrate that SFCMon introduces a negligible performance penalty while providing significant scalability gains.

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“…One solution to this problem is to keep track of only the large/heavy flows. A large flow is a flow that includes more than a certain percentage of the packets during a given time interval . Studies have shown that the majority of flows tend to be short (mice flows) on high‐speed links.…”

Section: Introductionmentioning

confidence: 99%

A real‐time attack defense framework for 5G network slicing

et al. 2020

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Network Slicing (NS) is a key enabler to support 5G network services on-demand. However, since NS is a result of the recent advancement in Software-Defined Networking and Network Function Virtualization, it introduces new security issues which include attacks against an NS instance within an operator network and interslice security threats. In this scenario, identifying and mitigating attacks in real-time is of paramount importance to improve security aspects. However, it is far from being straightforward. Therefore, this work proposes the FrameRTP4, a P4-based framework that aims to deliver real-time attack detection and mitigation mechanisms in 5G NS scenarios. For this, it provides a P4-based switch that implements an Service Function Chaining protocol layer, an efficient and scalable Access Control List for the detection and mitigation of known attacks, and a monitoring system aiming to reduce the overhead induced on the control channel. Furthermore, it delivers an orchestrator that aims to control all switches in order to enable lifecycle management of NS instances and P4 table rules. Besides, it also performs some autonomous tasks such as the wildcard rules generation and the detection of new threats by using machine learning algorithms. Preliminary results point to the potential benefits of FrameRTP4 to be part of a 5G NS infrastructure. K E Y W O R D S5G, bloom filter, cybersecurity, network function virtualization, network slice, P4

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Detecting heavy flows in the SDN match and action model

Cited by 56 publications

References 13 publications

Sonum: Software-Defined Synergetic Sampling Approach and Optimal Network Utilization Mechanism for Long Flow in a Data Center Network

Sonum: Software-Defined Synergetic Sampling Approach and Optimal Network Utilization Mechanism for Long Flow in a Data Center Network

SFCMon: An Efficient and Scalable Monitoring System for Network Flows in SFC-enabled Domains

A real‐time attack defense framework for 5G network slicing

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