@inproceedings{96d19a49ef4941d8a469654e8db957e5,
title = "Deriving Machine to Machine (M2M) Traffic Model from Communication Model",
abstract = "The typical traffic models proposed in literature can be considered as heuristic models since they only reflect the stochastic characteristic of the generated traffic. In this paper, we propose a model for M2M communications that generates the traffic. Therefore, the proposed model is able to capture a wider picture than the state-of-the-art traffic models. The proposed model illustrates the behaviour of M2M uplink communication in a network with multiple-access limited information capacity shared channels. In this paper, we analyzed the number of transmitted packets using the traffic model extracted from our proposed communication model and compared it with the state-of- the-art traffic models using simulations. The simulation results show that the proposed model has a significantly higher accuracy in estimating the number of transmitted packets compared with the liteature model.",
keywords = "Communication Model, Communication System Traffic, Machine to Machine Communication, Stochastic Process, Traffic Model",
author = "Basel Barakat and Simeon Keates and Kamran Arshad and Wassell, \{Ian J.\}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 5th International Symposium on Innovation in Information and Communication Technology, ISIICT 2018 ; Conference date: 31-10-2018 Through 01-11-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ISIICT.2018.8613727",
language = "English",
series = "5th International Symposium on Innovation in Information and Communication Technology, ISIICT 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "5th International Symposium on Innovation in Information and Communication Technology, ISIICT 2018",
address = "United States",
}