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Ieee Access Special Section Editorial: Artificial Intelligence Enabled Networking
Information Technology University Punjab, Lahore, Pakistan.
Department of Computer Science and Networked Systems, Faculty of Science and Technology, Sunway University, Kuala Lumpur, Malaysia.
Centre for Communication Systems Research, University of Surrey, UK.
School of Computing and Communications, Lancaster University, Lancaster, UK.
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2015 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 3, p. 3079-3082Article in journal, Editorial material (Other academic) Published
Abstract [en]

With today’s computer networks becoming increasingly dynamic, heterogeneous, and complex, there is great interest in deploying artificial intelligence (AI) based techniques for optimization and management of computer networks. AI techniques—that subsume multidisciplinary techniques from machine learning, optimization theory, game theory, control theory, and meta-heuristics—have long been applied to optimize computer networks in many diverse settings. Such an approach is gaining increased traction with the emergence of novel networking paradigms that promise to simplify network management (e.g., cloud computing, network functions virtualization, and software-defined networking) and provide intelligent services (e.g., future 5G mobile networks). Looking ahead, greater integration of AI into networking architectures can help develop a future vision of cognitive networks that will show network-wide intelligent behavior to solve problems of network heterogeneity, performance, and quality of service (QoS).

Place, publisher, year, edition, pages
IEEE, 2015. Vol. 3, p. 3079-3082
National Category
Computer Sciences
Research subject
Pervasive Mobile Computing
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URN: urn:nbn:se:ltu:diva-112003DOI: 10.1109/access.2015.2507798ISI: 000371388200237Scopus ID: 2-s2.0-84981187617OAI: oai:DiVA.org:ltu-112003DiVA, id: diva2:1944408
Available from: 2025-03-13 Created: 2025-03-13 Last updated: 2025-10-21Bibliographically approved

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Vasilakos, Athanasios V.

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