Prediction of Faults in Cellular Networks Using Bayesian Network Model

Kogeda, OP; Agbinya, JI

Prediction of Faults in Cellular Networks Using Bayesian Network Model

Kogeda, OP Agbinya, JI

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Publication Type:: Conference
Issue Date:: 2007-03-12T22:05:35Z

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Field	Value	Language
dc.contributor.author	Kogeda, OP	en_AU
dc.contributor.author	Agbinya, JI	en_AU
dc.date.accessioned	2007-03-12T22:05:35Z
dc.date.accessioned	2012-12-15T02:29:40Z
dc.date.available	2007-03-12T22:05:35Z
dc.date.available	2012-12-15T02:29:40Z
dc.date.issued	2007-03-12T22:05:35Z
dc.identifier.uri	http://hdl.handle.net/10453/19637
dc.description.abstract	Cellular network service providers compete with each other for the vast and dynamic market that is characterized by the ever-changing services on offer and technology. These services require very reliable net-works that can meet the customer service level of agreement (SLA). We are motivated by this to model the cellular network service faults and this paper reports on results of faults prediction modelling. Cellular networks are uncertain in their behaviours and therefore we use a Bayesian network to model them. We derive probabilistic models of the cellular network system in which the independence of relations between the variables of inter-est are represented explicitly. We use a directed graph in which two nodes are connected by an edge if one is a direct cause of the other. We present the simulation results of the study.	en_AU
dc.format.extent	256104 bytes
dc.format.mimetype	application/pdf
dc.language.iso	en_AU
dc.relation.replaces	http://hdl.handle.net/2100/97
dc.title	Prediction of Faults in Cellular Networks Using Bayesian Network Model	en_AU
dc.type	Conference
utslib.copyright.status	open_access

Abstract:

Cellular network service providers compete with each other for the vast and dynamic market that is characterized by the ever-changing services on offer and technology. These services require very reliable net-works that can meet the customer service level of agreement (SLA). We are motivated by this to model the cellular network service faults and this paper reports on results of faults prediction modelling. Cellular networks are uncertain in their behaviours and therefore we use a Bayesian network to model them. We derive probabilistic models of the cellular network system in which the independence of relations between the variables of inter-est are represented explicitly. We use a directed graph in which two nodes are connected by an edge if one is a direct cause of the other. We present the simulation results of the study.

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http://hdl.handle.net/10453/19637