{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/understanding-the-modeling-of-computer","title":"Understanding the Modeling of Computer Network Delays using Neural Networks","arxiv_id":"1807.08652","date":"2018-07-23","proceeding":null,"authors":["Albert Mestres","Eduard Alarcón","Yusheng Ji","Albert Cabellos-Aparicio"],"abstract":"Recent trends in networking are proposing the use of Machine Learning (ML)\ntechniques for the control and operation of the network. In this context, ML\ncan be used as a computer network modeling technique to build models that\nestimate the network performance. Indeed, network modeling is a central\ntechnique to many networking functions, for instance in the field of\noptimization, in which the model is used to search a configuration that\nsatisfies the target policy. In this paper, we aim to provide an answer to the\nfollowing question: Can neural networks accurately model the delay of a\ncomputer network as a function of the input traffic? For this, we assume the\nnetwork as a black-box that has as input a traffic matrix and as output delays.\nThen we train different neural networks models and evaluate its accuracy under\ndifferent fundamental network characteristics: topology, size, traffic\nintensity and routing. With this, we aim to have a better understanding of\ncomputer network modeling with neural nets and ultimately provide practical\nguidelines on how such models need to be trained.","url_abs":"http://arxiv.org/abs/1807.08652v1","url_pdf":"http://arxiv.org/pdf/1807.08652v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"understanding-the-modeling-of-computer","repo_url":"https://github.com/filipkrasniqi/QoSML","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}