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Títol:
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Understanding the modeling of computer network delays using neural networks
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Autor/a:
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Mestres Sugrañes, Albert; Alarcón Cot, Eduardo José; Ji, Y.; Cabellos Aparicio, Alberto
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Altres autors:
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Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors; Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla; Universitat Politècnica de Catalunya. EPIC - Energy Processing and Integrated Circuits |
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Abstract:
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The final publication is available at ACM via http://dx.doi.org/10.1145/3229607.3229613 |
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Abstract:
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Recent trends in networking are proposing the use of Machine Learning (ML) techniques for the control and operation of the network. In this context, ML can be used as a computer network modeling technique to build models that estimate the network performance. Indeed, network modeling is a central technique to many networking functions, for instance in the field of optimization, in which the model is used to search a configuration that satisfies the target policy. In this paper, we aim to provide an answer to the following question: Can neural networks accurately model the delay of a computer network as a function of the input traffic? For this, we assume the network as a black-box that has as input a traffic matrix and as output delays. Then we train different neural networks models and evaluate its accuracy under different fundamental network characteristics: topology, size, traffic intensity and routing. With this, we aim to have a better understanding of computer network modeling with neural nets and ultimately provide practical guidelines on how such models need to be trained. |
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Abstract:
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Peer Reviewed |
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Matèries:
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-Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Aprenentatge automàtic
-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
-Machine learning
-Computer networks
-KDN
-ML
-Modeling
-Networking
-SDN
-Artificial intelligence
-Big data
-Computer networks
-Convolutional codes
-Learning systems
-Models
-Network characteristics
-Network modeling
-Networking
-Neural networks model
-Practical guidelines
-Recent trends
-Traffic intensity
-Traffic matrices
-Data communication systems
-Aprenentatge automàtic
-Ordinadors, Xarxes d' |
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Drets:
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Tipus de document:
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Article - Versió presentada
Objecte de conferència |
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Publicat per:
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Association for Computing Machinery (ACM)
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Compartir:
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