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A New Modelling Approach to Represent the DCF Mechanism of the CSMA/CA Protocol

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Analytical and Stochastic Modelling Techniques and Applications (ASMTA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNPSE,volume 10378))

Abstract

In this paper, a Markovian agent model is used to represent the behavior of wireless nodes based on CSMA/CA access method. This kind of network was usually modeled by means of bidimensional Markov Chains and more recently using semi-Markov process based models. Both these approaches are based on the assumptions of both full load network and independence of collision probability with respect to retransmission count of each packet. Our model inherently releases the latter hypothesis since it is not necessary to establish a constant collision probability at steady state.

Here, we investigate the correctness of our approach analyzing the throughput of a network based on two IEEE 802.11g nodes when the amount of traffic sent by each one varies. Results have been compared with Omnet++ simulations and show the validity of the proposed model.

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Notes

  1. 1.

    From this point on, we use the terms station and wireless node interchangeably.

References

  1. IEEE Std 802.11-2012: IEEE Standard for Information technology-telecommunications and information exchange between systems Local and metropolitan area networks-Specific requirements part 11: wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications, (Revision of IEEE Std 802.11-2007), pp. 1–2793, March 2012

    Google Scholar 

  2. Bianchi, G.: Performance analysis of the IEEE 802.11 distributed coordination function. IEEE J. Sel. Areas Commun. 18(3), 535–547 (2000)

    Article  Google Scholar 

  3. Kadiyala, M.K., Shikha, D., Pendse, R., Jaggi, N.: Semi-Markov process based model for performance analysis of wireless LANs. In: 2011 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops), pp. 613–618, March 2011

    Google Scholar 

  4. Wang, H., Kang, G., Huang, K.: An advanced Semi-Markov process model for performance analysis of wireless LANs. In: 2012 IEEE Vehicular Technology Conference (VTC Fall), pp. 1–5, September 2012

    Google Scholar 

  5. Prasad, Y.R.V., Pachamuthu, R.: Analytical model of adaptive CSMA-CA MAC for reliable and timely clustered wireless multi-hop communication. In: 2014 IEEE World Forum on Internet of Things (WF-IoT), pp. 212–217, March 2014

    Google Scholar 

  6. Felemban, E., Ekici, E.: Single hop IEEE 802.11 DCF analysis revisited: accurate modeling of channel access delay and throughput for saturated and unsaturated traffic cases. IEEE Trans. Wirel. Commun. 10(10), 3256–3266 (2011)

    Article  Google Scholar 

  7. Lin, S., Fu, L.: Unsaturated throughput analysis of physical-layer network coding based on IEEE 802.11 distributed coordination function. IEEE Trans. Wirel. Commun. 12(11), 5544–5556 (2013)

    Article  Google Scholar 

  8. Tadayon, N., Wang, H., Chen, H.H.: Performance analysis of distributed access multihop poisson networks. IEEE Trans. Veh. Technol. 63(2), 849–858 (2014)

    Article  Google Scholar 

  9. Stajkic, A., Buratti, C., Verdone, R.: Modeling multi-hop CSMA-based networks through semi-Markov chains. In: 2015 International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 520–525, August 2015

    Google Scholar 

  10. Gribaudo, M., Cerotti, D., Bobbio, A.: Analysis of on-off policies in sensor networks using interacting markovian agents. In: Sixth Annual IEEE International Conference on Pervasive Computing and Communications, 2008. PerCom 2008, pp. 300–305, March 2008

    Google Scholar 

  11. Bruneo, D., Scarpa, M., Bobbio, A., Cerotti, D., Gribaudo, M.: Markovian agent modeling swarm intelligence algorithms in wireless sensor networks. Performance Evaluation 69(3–4), 135–149 (2012). Selected papers from ValueTools 2009. http://www.sciencedirect.com/science/article/pii/S0166531611000137

    Article  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Engineering, University of Messina, Contrada di Dio, 98166, S. Agata, Messina, Italy

    Marco Scarpa & Salvatore Serrano

Authors
  1. Marco Scarpa
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  2. Salvatore Serrano
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Corresponding author

Correspondence to Marco Scarpa .

Editor information

Editors and Affiliations

  1. School of Computing Science, Newcastle University, Newcastle upon Tyne, UK

    Nigel Thomas

  2. School of Computing Science, Newcastle University, Newcastle upon Tyne, UK

    Matthew Forshaw

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Scarpa, M., Serrano, S. (2017). A New Modelling Approach to Represent the DCF Mechanism of the CSMA/CA Protocol. In: Thomas, N., Forshaw, M. (eds) Analytical and Stochastic Modelling Techniques and Applications. ASMTA 2017. Lecture Notes in Computer Science(), vol 10378. Springer, Cham. https://doi.org/10.1007/978-3-319-61428-1_13

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  • DOI: https://doi.org/10.1007/978-3-319-61428-1_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-61427-4

  • Online ISBN: 978-3-319-61428-1

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