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- Title
Editorial.
- Authors
Pardalos, Panos; Kalyagin, Valery; Guarracino, Mario R.
- Abstract
This article discusses the significance of big data in modern networks and its impact on network management and optimization. It emphasizes how big data analytics can assist network operators in monitoring and analyzing network traffic, identifying anomalies, and optimizing network performance. The article also mentions various topics related to network models, such as obnoxious facility location, distributed optimization, multi-armed bandit problems, market networks, traffic forecasting, and decentralized optimization. These topics provide insights and methodologies for understanding and utilizing networked systems in different domains. The article serves as a citation for two articles published in the journal "Computational Management Science." The first article focuses on decentralized convex optimization on time-varying networks with an application to Wasserstein barycenters, while the second article is a publisher's note from Springer Nature, expressing their neutrality regarding jurisdictional claims and institutional affiliations.
- Subjects
MULTI-armed bandit problem (Probability theory); COMPUTER network traffic; COST functions; RATE of return on stocks; PARKINSON'S disease; NONSMOOTH optimization
- Publication
Computational Management Science, 2024, Vol 21, Issue 1, p1
- ISSN
1619-697X
- Publication type
Editorial
- DOI
10.1007/s10287-024-00518-x