A novel approach for performance-based clustering and anagement of network traffic flows

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A novel approach for performance-based clustering and anagement of network traffic flows

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M. Al-Saadi, B.V. Ghita, S. Shiaeles, P. Sarigiannidis: A novel approach for performance-based clustering and anagement of network traffic flows. 2019.

Περίληψη

Management of network performance comprises numerous functions such as measuring, modelling, planning and optimising networks to ensure that they transmit traffic with the speed, capacity and reliability expected by the applications, each with different requirements for bandwidth and delay. Overall, the objective of this paper is to propose a novel mechanism to optimise the network resource allocation through supporting the routing of individual flows, by clustering them based on performance and integrating the respective clusters with an SDN scheme. In this paper we have employed a particular set of traffic features then applied data reduction and unsupervised machine learning techniques, to derive an Internet traffic performance-based clustering model. Finally, the resulting data clusters are integrated within a unified SDN architectural solution, which improves network management by finding nearly optimal flow routing, to be evaluated against a number of traffic data sources. © 2019 IEEE.

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BibTeX (Download)

@conference{Al-Saadi20192025,
title = {A novel approach for performance-based clustering and anagement of network traffic flows},
author = { M. Al-Saadi and B.V. Ghita and S. Shiaeles and P. Sarigiannidis},
url = {https://www.researchgate.net/publication/334634109_A_novel_approach_for_performance-based_clustering_and_anagement_of_network_traffic_flows},
doi = {10.1109/IWCMC.2019.8766728},
year  = {2019},
date = {2019-01-01},
journal = {2019 15th International Wireless Communications and Mobile Computing Conference, IWCMC 2019},
pages = {2025-2030},
abstract = {Management of network performance comprises numerous functions such as measuring, modelling, planning and optimising networks to ensure that they transmit traffic with the speed, capacity and reliability expected by the applications, each with different requirements for bandwidth and delay. Overall, the objective of this paper is to propose a novel mechanism to optimise the network resource allocation through supporting the routing of individual flows, by clustering them based on performance and integrating the respective clusters with an SDN scheme. In this paper we have employed a particular set of traffic features then applied data reduction and unsupervised machine learning techniques, to derive an Internet traffic performance-based clustering model. Finally, the resulting data clusters are integrated within a unified SDN architectural solution, which improves network management by finding nearly optimal flow routing, to be evaluated against a number of traffic data sources. © 2019 IEEE.},
keywords = {Clustering, Network performance, SDN, Unsupervised algorithm},
pubstate = {published},
tppubtype = {conference}
}
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