A Visualization Tool for Analyzing the Design of Physical and Network Layers Parameters of a Wireless Network
The use of wireless networks (WLANs, femtocells, Wimax), as well as the increasing use of multimedia applications have grown fast in recent years. Some factors affect the quality of service (QoS) received by the user such as interference. This paper presents a novel data visualization tool for performance evaluation of wireless networks aiding analysis and design of their networks, considering relevant parameters from both physical and network layers (power, jitter, packet loss, delay and PMOS). The performance evaluation is achieved in three steps: measurement, computational intelligence approach through Bayesian networks and mathematical model. The measurement was done implementing an empirical study of the quality of services (QoS) parameters of a VoIP application in the presence of an interference network. Thus, this work is based on a hybrid approach that considers measuring and conditional probability tables, generated from a Bayesian Network, applied to wireless networks, considering QoS parameters. In this work an indoor environment was used to be analyzed but other wireless networks can make use of this visualization tool.
KeywordsConditional probability Wireless network Computational intelligence Bayesian networks
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- 1.ITU-T, “Measuring the Information Society” (2012), http://www.itu.int/ITU-D/ict/publications/idi/2010/Material/MIS_2010_without_annex_4-e.pdf (access in January 18, 2012)
- 4.Wang, Y., Cuthbert, L.G., Bigham, J.: Intelligent radio resource management for IEEE 802.11 WLAN. In: Proc. IEEE Wireless Communications and Networking Conf (WCNC 2004), vol. 3, pp. 1365–1370 (2004)Google Scholar
- 6.Lu, J.L., Jaffrés-Runser, K., Gorce, J.M., Valois, F.: Indoor WLAN planning with a QoS Constraint based on a Markovian Performance Evaluation Model. In: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 152–158 (2006)Google Scholar
- 7.Lu, J.L., Valois, F.: Performance evaluation of 802.11 WLAN in a real indoor environment. In: IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, pp. 140–147 (2006)Google Scholar
- 8.Chen, Z.: Data Mining and Uncertain Reasoning - an Integrated Approach. John Wiley Professional (2001)Google Scholar
- 9.Korb, K.B., Nicholson, A.E.: Bayesian Artificial Intelligence. CRC Press (2004)Google Scholar
- 10.Pearl, J.: Probabilistic Reasoning in Intelligent System. Morgan Kaufmann Publishers (1988)Google Scholar
- 11.MATLAB, Matlab version 7.0. In Technical Documentation (2012)Google Scholar