NDLI: Estimating heterogeneous traffics in CSMA networks at runtime

Content Provider	IEEE Xplore Digital Library
Author	Shuanglong Xie Kay-Soon Low Gunawan, E.
Copyright Year	2015
Description	Author affiliation: Sch. of Electr. & Electron. Eng., Nanyang Technol. Univ., Singapore, Singapore (Shuanglong Xie; Kay-Soon Low; Gunawan, E.)
Abstract	The efficient utilization of CSMA/CA network has been shown to heavily depend on the knowledge on the traffic loads of other nodes in the network. In a purely distributed network, the on-going traffic loads can only be estimated by exploiting locally available information. However, existing estimation algorithms are mainly focused on traffic estimation of homogeneous networks and when extending to heterogeneous networks the existing techniques are not applicable. In this paper, a novel heterogeneous Markov chain model is proposed to relate the two types of local information, namely clear channel assessment (CCA) result and acknowledgment (ACK) packet, to two variables characterizing the on-going traffic loads, namely the aggregate transmission rates and aggregate traffic loads. An improved particle filtering technique named Autoregressive Moving Average Particle Filter (ARMA-PF) is used to perform traffic estimation. It has been shown that the proposed method is accurate in characterizing the traffic loads and outperforms the existing methods.
Starting Page	226
Ending Page	231
File Size	294415
Page Count	6
File Format	PDF
e-ISBN	9781479984985
DOI	10.1109/TSP.2015.7296257
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-09
Publisher Place	Czech Republic
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Carrier Sensing Smoothing methods Aggregates Heterogeneous Networks Estimation Markov Chain Markov processes CSMA Multiaccess communication Autoregressive processes Load modeling
Content Type	Text
Resource Type	Article

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