The control of communication networks is an important aspect from both the service provider and user points of view. There are several approaches to communication network control including game theory, genetic algorithms and Markov decision processes. Data mining methods have been successfully used to discover optimized solutions to this problem, and have the capability to learn the network behavior under different network conditions and during operation so that complete knowledge of the network behavior is not required a priori. This article identifies the concepts behind the idea of using data mining for communication network control, provides a structured survey of the results in this area, and discusses the guidelines for future applications.
Data Mining Algorithms for Communication Networks Control: Concepts, Survey and Guidelines / De Sanctis, M; Bisio, I; Araniti, Giuseppe. - In: IEEE NETWORK. - ISSN 0890-8044. - 30:1(2016), pp. 24-29. [10.1109/MNET.2016.7389827]
Data Mining Algorithms for Communication Networks Control: Concepts, Survey and Guidelines
ARANITI, Giuseppe
2016-01-01
Abstract
The control of communication networks is an important aspect from both the service provider and user points of view. There are several approaches to communication network control including game theory, genetic algorithms and Markov decision processes. Data mining methods have been successfully used to discover optimized solutions to this problem, and have the capability to learn the network behavior under different network conditions and during operation so that complete knowledge of the network behavior is not required a priori. This article identifies the concepts behind the idea of using data mining for communication network control, provides a structured survey of the results in this area, and discusses the guidelines for future applications.File | Dimensione | Formato | |
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