Stochastic analysis of wireless sensor networks becomes exceedingly hard as the number of nodes in a network grows large. In this paper we intend to address this issue by proposing a method of modeling large networks by dynamical systems rather than explicit Markov models, called Mean-Field Approximation. We verify the suitability of Mean-Field Approximation by analyzing ALOHA, by both studying a discrete model and a system of differential equations and then by comparing these models. We then extend the modeling technique in order to express characteristics of a network running a CSMA/CA protocol.
|Titel||2015 IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT), 24 November 2015, Luxembourg City|
|Plaats van productie||Piscataway|
|Uitgeverij||Institute of Electrical and Electronics Engineers|
|Status||Gepubliceerd - 24 nov 2015|
Talebi, M., Groote, J. F., & Linnartz, J-P. (2015). Continuous approximation of stochastic models for wireless sensor networks. In 2015 IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT), 24 November 2015, Luxembourg City (blz. 1-6). Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SCVT.2015.7374240