ABSTRACT
Analyzing network topologies and communication graphs is essential in modern network management. However, the lack of a cohesive approach results in a steep learning curve, increased errors, and inefficiencies. In this paper, we present a novel approach that enables natural-language-based network management experiences, leveraging large language models (LLMs) to generate task-specific code from natural language queries. This method addresses the challenges of explainability, scalability, and privacy by allowing network operators to inspect the generated code, removing the need to share network data with LLMs, and focusing on application-specific requests combined with program synthesis techniques. We develop and evaluate a prototype system using benchmark applications, demonstrating high accuracy, cost-effectiveness, and potential for further improvements using complementary program synthesis techniques.
- Rohan Anil, Andrew M. Dai, Orhan Firat, Melvin Johnson, Dmitry Lepikhin, Alexandre Passos, Siamak Shakeri, Emanuel Taropa, Paige Bailey, Zhifeng Chen, Eric Chu, Jonathan H. Clark, Laurent El Shafey, Yanping Huang, Kathy Meier-Hellstern, Gaurav Mishra, Erica Moreira, Mark Omernick, Kevin Robinson, Sebastian Ruder, Yi Tay, Kefan Xiao, Yuanzhong Xu, Yujing Zhang, Gustavo Hernández Ábrego, Junwhan Ahn, Jacob Austin, Paul Barham, Jan A. Botha, James Bradbury, Siddhartha Brahma, Kevin Brooks, Michele Catasta, Yong Cheng, Colin Cherry, Christopher A. Choquette-Choo, Aakanksha Chowdhery, Clément Crepy, Shachi Dave, Mostafa Dehghani, Sunipa Dev, Jacob Devlin, Mark Díaz, Nan Du, Ethan Dyer, Vladimir Feinberg, Fangxiaoyu Feng, Vlad Fienber, Markus Freitag, Xavier Garcia, Sebastian Gehrmann, Lucas Gonzalez, and et al. 2023. PaLM 2 Technical Report. CoRR abs/2305.10403 (2023).Google Scholar
- Jacob Austin, Augustus Odena, Maxwell I. Nye, Maarten Bosma, Henryk Michalewski, David Dohan, Ellen Jiang, Carrie J. Cai, Michael Terry, Quoc V. Le, and Charles Sutton. 2021. Program Synthesis with Large Language Models. CoRR abs/2108.07732 (2021).Google Scholar
- John W. Backus, Robert J. Beeber, Sheldon Best, Richard Goldberg, Lois M. Haibt, Harlan L. Herrick, Robert A. Nelson, David Sayre, Peter B. Sheridan, H. Stern, Irving Ziller, Robert A. Hughes, and R. Nutt. 1957. The FORTRAN automatic coding system. In The 1957 western joint computer conference: Techniques for reliability (IRE-AIEE-ACM).Google Scholar
- Matej Balog, Alexander L. Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow. 2017. DeepCoder: Learning to Write Programs. In Proceedings of 5th International Conference on Learning Representations (ICLR).Google Scholar
- Ryan Beckett, Aarti Gupta, Ratul Mahajan, and David Walker. 2017. A General Approach to Network Configuration Verification. In Proceedings of the Conference of the ACM Special Interest Group on Data Communication (SIGCOMM).Google ScholarDigital Library
- Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020. Language Models are Few-Shot Learners. In Advances in Neural Information Processing Systems (NeurIPS).Google Scholar
- Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott M. Lundberg, Harsha Nori, Hamid Palangi, Marco Túlio Ribeiro, and Yi Zhang. 2023. Sparks of Artificial General Intelligence: Early experiments with GPT-4. CoRR abs/2303.12712 (2023).Google Scholar
- Angelica Chen, Jérémy Scheurer, Tomasz Korbak, Jon Ander Campos, Jun Shern Chan, Samuel R. Bowman, Kyunghyun Cho, and Ethan Perez. 2023. Improving Code Generation by Training with Natural Language Feedback. CoRR abs/2303.16749 (2023).Google Scholar
- Bei Chen, Fengji Zhang, Anh Nguyen, Daoguang Zan, Zeqi Lin, Jian-Guang Lou, and Weizhu Chen. 2022. CodeT: Code Generation with Generated Tests. CoRR abs/2207.10397 (2022).Google Scholar
- Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Pondé de Oliveira Pinto, Jared Kaplan, Harrison Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, Alex Ray, Raul Puri, Gretchen Krueger, Michael Petrov, Heidy Khlaaf, Girish Sastry, Pamela Mishkin, Brooke Chan, Scott Gray, Nick Ryder, Mikhail Pavlov, Alethea Power, Lukasz Kaiser, Mohammad Bavarian, Clemens Winter, Philippe Tillet, Felipe Petroski Such, Dave Cummings, Matthias Plappert, Fotios Chantzis, Elizabeth Barnes, Ariel Herbert-Voss, William Hebgen Guss, Alex Nichol, Alex Paino, Nikolas Tezak, Jie Tang, Igor Babuschkin, Suchir Balaji, Shantanu Jain, William Saunders, Christopher Hesse, Andrew N. Carr, Jan Leike, Joshua Achiam, Vedant Misra, Evan Morikawa, Alec Radford, Matthew Knight, Miles Brundage, Mira Murati, Katie Mayer, Peter Welinder, Bob McGrew, Dario Amodei, Sam McCandlish, Ilya Sutskever, and Wojciech Zaremba. 2021. Evaluating Large Language Models Trained on Code. CoRR abs/2107.03374 (2021).Google Scholar
- Xinyun Chen, Maxwell Lin, Nathanael Schärli, and Denny Zhou. 2023. Teaching Large Language Models to Self-Debug. CoRR abs/2304.05128 (2023).Google Scholar
- Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022. PaLM: Scaling Language Modeling with Pathways. CoRR abs/2204.02311 (2022).Google Scholar
- Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, and John Schulman. 2021. Training Verifiers to Solve Math Word Problems. CoRR abs/2110.14168 (2021).Google Scholar
- Chris J Date. 1989. A Guide to the SQL Standard. Addison-Wesley Longman Publishing Co., Inc.Google ScholarDigital Library
- NetworkX Developers. NetworkX: Network Analysis in Python. https://networkx.org/, Retrieved on 2023-02.Google Scholar
- Tyna Eloundou, Sam Manning, Pamela Mishkin, and Daniel Rock. 2023. GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models. CoRR abs/2303.10130 (2023).Google Scholar
- Ari Fogel, Stanley Fung, Luis Pedrosa, Meg Walraed-Sullivan, Ramesh Govindan, Ratul Mahajan, and Todd D. Millstein. 2015. A General Approach to Network Configuration Analysis. In 12th USENIX Symposium on Networked Systems Design and Implementation (NSDI).Google Scholar
- Daniel Fried, Armen Aghajanyan, Jessy Lin, Sida Wang, Eric Wallace, Freda Shi, Ruiqi Zhong, Wen-tau Yih, Luke Zettlemoyer, and Mike Lewis. 2022. InCoder: A Generative Model for Code Infilling and Synthesis. CoRR abs/2204.05999 (2022).Google Scholar
- Eduard Glatz, Stelios Mavromatidis, Bernhard Ager, and Xenofontas A. Dimitropoulos. 2014. Visualizing big network traffic data using frequent pattern mining and hypergraphs. Computing 96, 1 (2014), 27--38.Google ScholarDigital Library
- Google. Google Bard. https://bard.google.com/, Retrieved on 2023-06.Google Scholar
- Google. MALT example models. https://github.com/google/malt-example-models, Retrieved on 2023-06.Google Scholar
- Sumit Gulwani. 2011. Automating string processing in spreadsheets using input-output examples. In Proceedings of the 38th ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL).Google ScholarDigital Library
- Sumit Gulwani, Oleksandr Polozov, and Rishabh Singh. 2017. Program Synthesis. Found. Trends Program. Lang. 4, 1-2 (2017).Google ScholarCross Ref
- Arpit Gupta, Rob Harrison, Marco Canini, Nick Feamster, Jennifer Rexford, and Walter Willinger. 2018. Sonata: query-driven streaming network telemetry. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM).Google ScholarDigital Library
- Marios Iliofotou, Prashanth Pappu, Michalis Faloutsos, Michael Mitzenmacher, Sumeet Singh, and George Varghese. 2007. Network monitoring using traffic dispersion graphs (TDGs). In Proceedings of the 7th ACM SIGCOMM Internet Measurement Conference (IMC).Google ScholarDigital Library
- Srinivasan Iyer, Ioannis Konstas, Alvin Cheung, Jayant Krishnamurthy, and Luke Zettlemoyer. 2017. Learning a Neural Semantic Parser from User Feedback. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL).Google ScholarCross Ref
- Srikanth Kandula, Dina Katabi, and Jean-Philippe Vasseur. 2005. Shrink: a tool for failure diagnosis in IP networks. In Proceedings of the 1st Annual ACM Workshop on Mining Network Data (MineNet).Google ScholarDigital Library
- Hyeonji Kim, Byeong-Hoon So, Wook-Shin Han, and Hongrae Lee. 2020. Natural language to SQL: Where are we today? Proc. VLDB Endow. 13, 10 (2020).Google ScholarDigital Library
- Do Quoc Le, Taeyoel Jeong, H. Eduardo Roman, and James Won-Ki Hong. 2011. Traffic dispersion graph based anomaly detection. In Proceedings of the Symposium on Information and Communication Technology (SoICT).Google ScholarDigital Library
- Sihyung Lee, Kyriaki Levanti, and Hyong S. Kim. 2014. Network monitoring: Present and future. Comput. Networks 65 (2014).Google Scholar
- Fei Li and H. V. Jagadish. 2014. Constructing an Interactive Natural Language Interface for Relational Databases. Proc. VLDB Endow. 8, 1 (2014).Google Scholar
- Raymond Li, Loubna Ben Allal, Yangtian Zi, Niklas Muennighoff, Denis Kocetkov, Chenghao Mou, Marc Marone, Christopher Akiki, Jia Li, Jenny Chim, Qian Liu, Evgenii Zheltonozhskii, Terry Yue Zhuo, Thomas Wang, Olivier Dehaene, Mishig Davaadorj, Joel Lamy-Poirier, João Monteiro, Oleh Shliazhko, Nicolas Gontier, Nicholas Meade, Armel Zebaze, Ming-Ho Yee, Logesh Kumar Umapathi, Jian Zhu, Benjamin Lipkin, Muhtasham Oblokulov, Zhiruo Wang, Rudra Murthy V, Jason Stillerman, Siva Sankalp Patel, Dmitry Abulkhanov, Marco Zocca, Manan Dey, Zhihan Zhang, Nour Moustafa-Fahmy, Urvashi Bhattacharyya, Wenhao Yu, Swayam Singh, Sasha Luccioni, Paulo Villegas, Maxim Kunakov, Fedor Zhdanov, Manuel Romero, Tony Lee, Nadav Timor, Jennifer Ding, Claire Schlesinger, Hailey Schoelkopf, Jan Ebert, Tri Dao, Mayank Mishra, Alex Gu, Jennifer Robinson, Carolyn Jane Anderson, Brendan Dolan-Gavitt, Danish Contractor, Siva Reddy, Daniel Fried, Dzmitry Bahdanau, Yacine Jernite, Carlos Muñoz Ferrandis, Sean Hughes, Thomas Wolf, Arjun Guha, Leandro von Werra, and Harm de Vries. 2023. StarCoder: may the source be with you! CoRR abs/2305.06161 (2023).Google Scholar
- Yujia Li, David H. Choi, Junyoung Chung, Nate Kushman, Julian Schrittwieser, Rémi Leblond, Tom Eccles, James Keeling, Felix Gimeno, Agustin Dal Lago, Thomas Hubert, Peter Choy, Cyprien de Masson d'Autume, Igor Babuschkin, Xinyun Chen, Po-Sen Huang, Johannes Welbl, Sven Gowal, Alexey Cherepanov, James Molloy, Daniel J. Mankowitz, Esme Sutherland Robson, Pushmeet Kohli, Nando de Freitas, Koray Kavukcuoglu, and Oriol Vinyals. 2022. Competition-Level Code Generation with AlphaCode. CoRR abs/2203.07814 (2022).Google Scholar
- Zohar Manna and Richard J. Waldinger. 1971. Toward Automatic Program Synthesis. Commun. ACM 14, 3 (1971).Google Scholar
- Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan T. McDonald. 2020. On Faithfulness and Factuality in Abstractive Summarization. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL).Google Scholar
- Microsoft. Azure OpenAI Service pricing. https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/, Retrieved on 2023-06.Google Scholar
- Microsoft. A guidance language for controlling large language models. https://github.com/microsoft/guidance, Retrieved on 2023-06.Google Scholar
- Microsoft. Introducing GitHub Copilot X. https://github.com/features/preview/copilot-x, Retrieved on 2023-06.Google Scholar
- Jeffrey C. Mogul, Drago Goricanec, Martin Pool, Anees Shaikh, Douglas Turk, Bikash Koley, and Xiaoxue Zhao. 2020. Experiences with Modeling Network Topologies at Multiple Levels of Abstraction. In USENIX Symposium on Networked Systems Design and Implementation (NSDI).Google Scholar
- Ansong Ni, Srini Iyer, Dragomir Radev, Ves Stoyanov, Wen-tau Yih, Sida I. Wang, and Xi Victoria Lin. 2023. LEVER: Learning to Verify Language-to-Code Generation with Execution. CoRR abs/2302.08468 (2023).Google Scholar
- NumFOCUS. pandas. https://pandas.pydata.org/, Retrieved on 2023-06.Google Scholar
- OpenAI. ChatGPT plugins. https://openai.com/blog/chatgpt-plugins, Retrieved on 2023-05.Google Scholar
- OpenAI. Code interpreter. https://openai.com/blog/chatgpt-plugins-code-interpreter, Retrieved on 2023-08.Google Scholar
- OpenAI. Introducing ChatGPT. https://openai.com/blog/chatgpt, Retrieved on 2023-02.Google Scholar
- OpenAI. OpenAI models. https://platform.openai.com/docs/models/overview, Retrieved on 2023-06.Google Scholar
- OpenAI. 2023. GPT-4 Technical Report. CoRR abs/2303.08774 (2023).Google Scholar
- Arjun Roy, Hongyi Zeng, Jasmeet Bagga, and Alex C. Snoeren. 2017. Passive Realtime Datacenter Fault Detection and Localization. In USENIX Symposium on Networked Systems Design and Implementation (NSDI).Google Scholar
- Freda Shi, Daniel Fried, Marjan Ghazvininejad, Luke Zettlemoyer, and Sida I. Wang. 2022. Natural Language to Code Translation with Execution. In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP).Google Scholar
- Noah Shinn, Federico Cassano, Beck Labash, Ashwin Gopinath, Karthik Narasimhan, and Shunyu Yao. 2023. Reflexion: Language Agents with Verbal Reinforcement Learning. CoRR abs/2303.11366 (2023).Google Scholar
- Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Kumar Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Schärli, Aakanksha Chowdhery, Philip Andrew Mansfield, Blaise Agüera y Arcas, Dale R. Webster, Gregory S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle K. Barral, Christopher Semturs, Alan Karthikesalingam, and Vivek Natarajan. 2022. Large Language Models Encode Clinical Knowledge. CoRR abs/2212.13138 (2022).Google Scholar
- Ruoxi Sun, Sercan Ö. Arik, Hootan Nakhost, Hanjun Dai, Rajarishi Sinha, Pengcheng Yin, and Tomas Pfister. 2023. SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL. CoRR abs/2306.00739 (2023).Google Scholar
- Hamid Tahaei, Firdaus Afifi, Adeleh Asemi, Faiz Zaki, and Nor Badrul Anuar. 2020. The rise of traffic classification in IoT networks: A survey. J. Netw. Comput. Appl. 154 (2020), 102538.Google ScholarDigital Library
- Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023. LLaMA: Open and Efficient Foundation Language Models. CoRR abs/2302.13971 (2023).Google Scholar
- Immanuel Trummer. 2022. CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex. Proc. VLDB Endow. 15, 11 (2022).Google ScholarDigital Library
- European Union. General Data Protection Regulation (GDPR). https://commission.europa.eu/law/law-topic/data-protection_en, Retrieved on 2023-04.Google Scholar
- Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models. In Advances in Neural Information Processing Systems (NeurIPS).Google Scholar
- Jules White, Sam Hays, Quchen Fu, Jesse Spencer-Smith, and Douglas C. Schmidt. 2023. ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design. CoRR abs/2303.07839 (2023).Google Scholar
- Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola. 2022. Automatic Chain of Thought Prompting in Large Language Models. CoRR abs/2210.03493 (2022).Google Scholar
- Wayne Xin Zhao, Kun Zhou, Junyi Li, Tianyi Tang, Xiaolei Wang, Yupeng Hou, Yingqian Min, Beichen Zhang, Junjie Zhang, Zican Dong, Yifan Du, Chen Yang, Yushuo Chen, Zhipeng Chen, Jinhao Jiang, Ruiyang Ren, Yifan Li, Xinyu Tang, Zikang Liu, Peiyu Liu, Jian-Yun Nie, and Ji-Rong Wen. 2023. A Survey of Large Language Models. CoRR abs/2303.18223 (2023).Google Scholar
- Yu Zhou, Chen Sun, Hongqiang Harry Liu, Rui Miao, Shi Bai, Bo Li, Zhilong Zheng, Lingjun Zhu, Zhen Shen, Yongqing Xi, Pengcheng Zhang, Dennis Cai, Ming Zhang, and Mingwei Xu. 2020. Flow Event Telemetry on Programmable Data Plane. In Proceedings of the Annual Conference of the ACM Special Interest Group on Data Communication (SIGCOMM).Google ScholarDigital Library
Index Terms
- Enhancing Network Management Using Code Generated by Large Language Models
Recommendations
Studies on network management system framework of campus network
CAR'10: Proceedings of the 2nd international Asia conference on Informatics in control, automation and robotics - Volume 2With the development of the computer network, and the great change in the demands of network management, any Network Management System is a process of development and perfection. Therefore, designing a rational system structure is the foundation to ...
The reliable distributed network management platform
FTDCS '95: Proceedings of the 5th IEEE Workshop on Future Trends of Distributed Computing SystemsAbstract: Outgrowth of the development of distributed computer environment has caused local resources to be connected and shared by means of networks. A user can utilize far much efficiently way through the networks. Without effective network management,...
Research on an Integrated Network Management System
SNPD '07: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 02Currently, multiform network management systems and complex network environment lead the network management system from traditional form for special network to multi-functional intelligent network management system. The paper gives an analysis of the ...
Comments