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Performance Analysis of Gamma/M/1 Model for IoT-Based Sensor Data Traffic | IEEE Journals & Magazine | IEEE Xplore

Performance Analysis of Gamma/M/1 Model for IoT-Based Sensor Data Traffic


Abstract:

Recent investigations of Internet of Things network traffic suggest the failure of traditionally used Poisson process-based models. The paper substantiates this finding b...Show More

Abstract:

Recent investigations of Internet of Things network traffic suggest the failure of traditionally used Poisson process-based models. The paper substantiates this finding by performing statistical analysis of packets inter-arrival time in publicly available datasets of IoT-based sensor data traffic. It is observed that gamma distribution fits well to the inter-arrival time of packets. Motivated by this outcome, a detailed performance evaluation of Gamma/M/1 model is carried out. The closed form expressions of mean queue length, mean waiting time in the queue and overflow probability are derived. Numerical computations show that the mean queue length of Gamma/M/1 model explodes much faster than Poisson process based M/M/1 model when its shape parameter is low and scale parameter is high, whereas, the opposite is observed when the values of parameters are reversed. Monte-Carlo simulation of the Gamma/M/1 model also validates these findings. These results will be useful in dimensioning resources like buffers and in designing congestion-control algorithms for IoT systems.
Published in: IEEE Wireless Communications Letters ( Volume: 10, Issue: 11, November 2021)
Page(s): 2430 - 2434
Date of Publication: 04 August 2021

ISSN Information:


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