Employing Bayesian Belief Networks for energy efficient Network Management
Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network ele...
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creator | Bashar, A. Parr, G.P. McClean, S.I. Scotney, B.W. Subramanian, M. Chaudhari, S.K. Gonsalves, T.A. |
description | Network Management Systems (NMS) are used to monitor the network and along with Operations Support Systems (OSS) maintain the performance with a focus on guaranteeing sustained QoS to the applications and services. One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance. |
doi_str_mv | 10.1109/NCC.2010.5430172 |
format | Conference Proceeding |
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One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. 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One aspect that is given less importance is the energy consumption of the network elements during the off peak periods. This paper looks at a scenario where the NMS plays an important role in making the network energy efficient by intelligently turning the network elements or their selective ports to sleep mode when they are underutilized. To this end, we propose and evaluate a Bayesian Belief Network (BBN) based Decision Management System (DMS), which provides intelligent decisions to the NMS for it to adaptively alter the operational modes of the network elements, without compromising the performance and QoS constraints. Simulated network has been used to provide the proof of concept followed by discussions on the amount of energy saved and its effect on the network performance.</abstract><pub>IEEE</pub><doi>10.1109/NCC.2010.5430172</doi><tpages>5</tpages></addata></record> |
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subjects | Bayesian Belief Networks (BBN) Bayesian methods Computer network management Energy consumption Energy efficiency Energy management Energy-aware Intelligent networks IP networks Network Management Next generation networking Quality of service Telecommunication computing |
title | Employing Bayesian Belief Networks for energy efficient Network Management |
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