ENERGY AWARE NETWORK: BAYESIAN BELIEF NETWORKS BASED DECISION MANAGEMENT SYSTEM

Abstract
A Network Management System (NMS) plays a very important role in managing an ever-evolving telecommunication network. Generally an NMS monitors & maintains the health of network elements. The growing size of the network warrants extra functionalities from the NMS. An NMS provides all kinds of information about networks which can be used for other purposes apart from monitoring & maintaining networks like improving QoS & saving energy in the network. In this paper, we add another dimension to NMS services, namely, making an NMS energy aware. We propose a Decision Management System (DMS) framework which uses a machine learning technique called Bayesian Belief Networks (BBN), to make the NMS energy aware. The DMS is capable of analysing and making control decisions based on network traffic. We factor in the cost of rerouting and power saving per port. Simulations are performed on standard network topologies, namely, ARPANet and IndiaNet. It is found that ~2.5-6.5% power can be saved.

Authors
Santosh Kumar Chaudhari1 and Hema A Murthy2
Indian Institute of Technology Madras, India

Keywords
Energy Aware Network Management System (EA-NMS), Next Generation Networks (NGN), Bayesian Belief Networks (BBN), Decision Management System (DMS)
Published By :
ICTACT
Published In :
ICTACT Journal on Communication Technology
( Volume: 2 , Issue: 2 )
Date of Publication :
June 2011

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