Automatic Definition and Application of Similarity Measures for Self-Operation of Network

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Date
2017-01
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Language
en
Pages
14
206-219
Series
Mobile Networks and Management, Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, Volume 191
Abstract
Self-operation concept is proposed to learn the past experiences of network operations and apply the learned operation experiences to solve new but similar problems. It works based upon the observation that actions appropriate for achieving an objective resemble each other in similar network contexts. Plenty of such similarities exist at the level of network elements, functions, and their relations. Similarity measure definition and application are essential components for the self-operation to apply the learned operation experiences. This paper provides a solution for self-operation to define and apply two types of similarity measures for two self-operation use cases. The first use case answers how to select a best suitable function to achieve any given objective. The second use case tells how the selected function should be configured with the most optimal parameter values so that the given objective could be achieved. This solution is realized on a demonstrator implementing the self-operation concept. Corresponding experiments are made with the demonstrator. The experimental results show that the solution works well for self-operation as expected.
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Tang , H , Stenberg , K , Apajalahti , K , Niiranen , J & Räisänen , V 2017 , Automatic Definition and Application of Similarity Measures for Self-Operation of Network . in Mobile Networks and Management : 8th International Conference, MONAMI 2016, Abu Dhabi, United Arab Emirates, October 23-24, 2016, Proceedings . Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering , vol. 191 , Springer , pp. 206-219 , International Conference on Mobile Networks and Management , Abu Dhabi , United Arab Emirates , 23/10/2016 . https://doi.org/10.1007/978-3-319-52712-3_15