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Ahmed, Saeed; Dukkipati, Nandita; Valancius, Vytautas; Contavalli, Carlo; Vahdat, Amin

doi:10.1145/3098822.3098852

Cited by 78 publications

(11 citation statements)

References 24 publications

(17 reference statements)

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“…In particular, bandwidth brokers are no longer needed to estimate application demands. Furthermore, rate allocations can, if necessary, be enforced by piggy-backing on novel traffic shaping techniques that are deployed in modern cloud servers at the OS-level as well as in NIC/FPGA offloads [1,12,43,47].…”

Section: Realizing Dotementioning

confidence: 99%

A Deep Learning Perspective on Network Routing

Perry¹,

Frujeri²,

Hoch³

et al. 2023

Preprint

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Routing is, arguably, the most fundamental task in computer networking, and the most extensively studied one.A key challenge for routing in real-world environments is the need to contend with uncertainty about future traffic demands. We present a new approach to routing under demand uncertainty: tackling this challenge as stochastic optimization, and employing deep learning to learn complex patterns in traffic demands. We show that our method provably converges to the global optimum in well-studied theoretical models of multicommodity flow. We exemplify the practical usefulness of our approach by zooming in on the real-world challenge of traffic engineering (TE) on wide-area networks (WANs). Our extensive empirical evaluation on real-world traffic and network topologies establishes that our approach's TE quality almost matches that of an (infeasible) omniscient oracle, outperforming previously proposed approaches, and also substantially lowers runtimes.

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Section: Realizing Dotementioning

confidence: 99%

A Deep Learning Perspective on Network Routing

Perry¹,

Frujeri²,

Hoch³

et al. 2023

Preprint

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“…9c). For instance, if the configured/expected rate is lower than 100 kbps, the measured burst size is slightly bigger (i.e., ∼ 12.5 kbits) than the maximal size of an ethernet packet (i.e., 1500 × 8 bits = 12 kbits) 4 . For the higher rates, the burst size corresponds to ∼ 12.5% of the configured rate.…”

Section: ) Burst Deviationmentioning

confidence: 99%

“…Indeed, unexpected bursts of traffic entering the network consumes bandwidth, build up queues, and potentially leads to unexpected packet losses and hence degraded performance for other tenants. To avoid that, operators rely on policing and/or shaping of the traffic at the edge of the network, typically performed directly on the end hosts [1]- [4].…”

Section: Introductionmentioning

confidence: 99%

Towards Understanding the Performance of Traffic Policing in Programmable Hardware Switches

Eeric

Varasteh

Bemten

et al. 2021

2021 IEEE 7th International Conference on Network Softwarization (NetSoft)

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To provide the predictability required by emerging applications, operators typically rely on policing and/or shaping at the edge to ensure that tenants do not use excess bandwidth that was not accounted for. One of the promises of 6G is to deploy applications with strict predictability requirements across subnets and even over the Internet, where policing cannot be implemented in the end hosts. This paper presents an empirical study of the ability of modern programmable network devices to implement predictable traffic policing in the network. We find out that none of the five investigated hardware switches can provide accurate traffic policing, a key requirement for providing predictable service to applications. We observe that the switches let applications send more than what they should be allowed to, reaching up to 60% and 100% relative error for the rate and burst parameters. We further uncover the fact that switches cannot police arbitrarily low bursts, e.g., not less than 13 kilobit for one of our switches. We investigate how such limitations impact the performance of state-of-the-art solutions for predictable latency such as Chameleon. We observe that, for ensuring its predictable guarantees, Chameleon rejects around 50% of the tenants it could accommodate if switches were perfect, hence decreasing by the same ratio the revenue for the operator. Based on these observations, we discuss solutions toward more accurate and predictable policing in wide-area networks.

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“…Other use cases for Libpreemptible include traffic shaping [61], scheduling in 5G [35], and real-time DNN serving [41]. The accuracy of these timed actions is crucial to the performance of these real-time application.…”

Section: B Other Use Cases and Future Workmentioning

confidence: 99%

Adaptive Task-Space Synchronization Control of SMMS Teleoperaiton Systems with Round-Robin Scheduling Protocol

Yin

et al. 2019

2019 Chinese Control Conference (CCC)

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Modern cloud applications are prone to high tail latencies since their requests typically follow highly-dispersive distributions. Prior work has proposed both OS-and systemlevel solutions to reduce tail latencies for microsecond-scale workloads through better scheduling. Unfortunately, existing approaches like customized dataplane OSes, require significant OS changes, experience scalability limitations, or do not reach the full performance capabilities hardware offers. We propose LibPreemptible, a preemptive user-level threading library that is flexible, lightweight, and scalable. LibPreemptible is based on three key techniques: 1) a fast and lightweight hardware mechanism for delivery of timed interrupts, 2) a general-purpose user-level scheduling interface, and 3) an API for users to express adaptive scheduling policies tailored to the needs of their applications. Compared to the prior state-of-the-art scheduling system Shinjuku, our system achieves significant tail latency and throughput improvements for various workloads without the need to modify the kernel. We also demonstrate the flexibility of LibPreemptible across scheduling policies for real applications experiencing varying load levels and characteristics.

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Cited by 78 publications

References 24 publications

A Deep Learning Perspective on Network Routing

A Deep Learning Perspective on Network Routing

Towards Understanding the Performance of Traffic Policing in Programmable Hardware Switches

Adaptive Task-Space Synchronization Control of SMMS Teleoperaiton Systems with Round-Robin Scheduling Protocol

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