The influence of interference networks in QoS parameters in a WLAN 802.11g: a Bayesian approach

Araújo, Jasmine Priscyla Leite de; Rodrigues, Josiane; Fraiha, Simone G. C.; Gomes, Cristiane Ruiz; Reis, Jacklyn; Vijaykumar, Nandamudi Lankalapalli; Cavalcante, Gervásio P. S.; Francês, Carlos Renato Lisboa

doi:10.1117/12.734604

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…This section discusses the measurements of the application and physical layers as well as the results obtained by Bayesian networks. The study involves processing the measured data with the Bayesian network technique [5]. In any process of knowledge discovery, there is a pre-analysis phase of processing (soft mining) the data where information that does not to contribute to the final result is removed.…”

Section: B Bayesian Inference Resultsmentioning

confidence: 99%

“…This has been established in ITU-T (International Telecommunication Union) New Strategies for Planning and Performance Evaluation of Wireless Networks: Case Studies Based on the Cross-layer Approach G.114 recommendation and in the Wang and Fang work [2]. Due to the rigid parameter requirements of the VoIP application, the protocol has been evaluated in several test beds [3]- [5].…”

Section: Introductionmentioning

confidence: 99%

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New strategies for planning and performance evaluation of wireless networks: case studies based on the cross-layer approach

Araújo

Rodrigues

Fraiha

et al. 2013

J. Microw. Optoelectron. Electromagn. Appl.

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The use of wireless local area networks, called WLANs, as well as the proliferation of the use of multimedia applications have grown rapidly in recent years. Some factors affect the quality of service (QoS) received by the user and interference is one of them. This work presents strategies for planning and performance evaluation through an empirical study of the QoS parameters of a voice over Internet Protocol (VoIP) application in an interference network, as well as the relevance in the design of wireless networks to determine the coverage area of an access point, taking into account several parameters such as power, jitter, packet loss, delay, and PMOS. Another strategy is based on a hybrid approach that considers measuring and Bayesian inference applied to wireless networks, taking into consideration QoS parameters. The models take into account a cross layer vision of networks, correlating aspects of the physical environment, on the signal propagation (power or distance) with aspects of VoIP applications (e.g., jitter and packet loss). Case studies were carried out for two indoor environments and two outdoor environments, one of them displaying main characteristics of the Amazon region (e.g., densely arboreous environments). This last test bed was carried out in a real system because the Government of the State of Pará has a digital inclusion program called NAVEGAPARÁ.

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Section: B Bayesian Inference Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New strategies for planning and performance evaluation of wireless networks: case studies based on the cross-layer approach

Araújo

Rodrigues

Fraiha

et al. 2013

J. Microw. Optoelectron. Electromagn. Appl.

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show abstract

“…The study involved treating the measured data acquired with the novel strategy using any intelligence computational technique, i.e. the Bayesian network technique (Araújo et al, 2007). In any process of knowledge discovery, there is a pre-analysis phase of treatment (soft mining) of the data where information that is not going to contribute to the final result are removed.…”

Section: Bayesian Inference Resultsmentioning

confidence: 99%

Strategy for Wireless Local Area Networks Planning and Performance Evaluation through Bayesian Networks as Computational Intelligence Approach

Araújo¹,

Rodrigues²,

Fraiha³

et al. 2010

Bayesian Network

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“…In previous works [14,15] the effect of interference in QoS parameters was studied using bayesian networks as computational intelligence method to quantify/characterize interference influence. In this work a hybrid optimization study was done with the use of genetic algorithms to improve the knowledge discovery process resulting from the bayesian approach.…”

Section: Introductionmentioning

confidence: 99%

A WLAN planning proposal through computational intelligence and genetic algorithms hybrid approach

Araújo

Rodrigues

Fraiha

et al. 2008

Proceedings of the International Conference on Mobile Technology, Applications, and Systems - Mobility '08

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This paper proposes a WLAN planning strategy through the use of computational intelligence and genetic algorithm. A measurement technique was used to collect data from a real WLAN network. Metrics like power, distance, delay, jitter, packet loss, throughput and PMOS were analysed through the use of bayesian networks. Finally, to optimize the QoS parameters a genetic algorithm was applied to find the best distance from the AP to support the QoS ITU-T recommendations.

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The influence of interference networks in QoS parameters in a WLAN 802.11g: a Bayesian approach

Cited by 5 publications

References 11 publications

New strategies for planning and performance evaluation of wireless networks: case studies based on the cross-layer approach

New strategies for planning and performance evaluation of wireless networks: case studies based on the cross-layer approach

Strategy for Wireless Local Area Networks Planning and Performance Evaluation through Bayesian Networks as Computational Intelligence Approach

A WLAN planning proposal through computational intelligence and genetic algorithms hybrid approach

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