NetBOA-Reference-Cited by-同舟云学术

NetBOA

Published:2019 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2019 Workshop on Network Meets AI & ML - NetAI'19
language:
Short-container-title:

Author:

Zerwas Johannes¹,Kalmbach Patrick¹,Henkel Laurenz¹,Rétvári Gábor²,Kellerer Wolfgang¹,Blenk Andreas¹,Schmid Stefan³

Affiliation:

1. Technical University of Munich, Germany

2. Budapest University of Technology and Economics, Hungary

3. University of Vienna, Austria

Funder

Horizon 2020

Deutsche Forschungsgemeinschaft

Publisher

ACM Press

Reference30 articles.

1. Omid Alipourfard, Hongqiang Harry Liu, Jianshu Chen, Shivaram Venkataraman, Minlan Yu, and Ming Zhang. 2017. CherryPick: Adaptively Unearthing the Best Cloud Configurations for Big Data Analytics. Proc. USENIX NSDI (2017), 469--482.

2. Simon Bauer, Daniel Raumer, Paul Emmerich, and Georg Carle. 2018. Behind the scenes: what device benchmarks can tell us. (2018).

3. Ryan Beckett, Aarti Gupta, Ratul Mahajan, and David Walker. 2017. A General Approach to Network Configuration Verification. In Proc. ACM SIGCOMM. Los Angeles, CA, USA, 155--168.

4. Andreas Blenk, Patrick Kalmbach, Stefan Schmid, and Wolfgang Kellerer. 2017. o'zapft is: Tap Your Network Algorithm's Big Data!. In Proc. ACM SIGCOMM Big-DAMA. Los Angeles, CA, USA.

5. S. Bradner and J. McQuaid. 1999. Benchmarking Methodology for Network Interconnect Devices. RFC 2544. (March 1999).

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. AdFAT: Adversarial Flow Arrival Time Generation for Demand-Oblivious Data Center Networks;2023 19th International Conference on Network and Service Management (CNSM);2023-10-30

2. AIDTN: Towards a Real-Time AI Optimized DTN System With NVMeoF;IEEE Transactions on Parallel and Distributed Systems;2023-06

3. Improving Intent Correctness with Automated Testing;2022 IEEE 8th International Conference on Network Softwarization (NetSoft);2022-06-27

4. Bayesian optimization and deep learning for steering wheel angle prediction;Scientific Reports;2022-05-24

5. In-Network Neural Networks: Challenges and Opportunities for Innovation;IEEE Network;2021-11