IoT 20(23): e4

Research Article

Statistical Analysis of a Distributed Queuing Random Access Protocol in a Massive Communication Environment

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  • @ARTICLE{10.4108/eai.16-10-2020.166663,
        author={Romeo Nibitanga and Elijah Mwangi and Edward Ndung’u},
        title={Statistical Analysis of a Distributed Queuing Random Access Protocol in a Massive Communication Environment},
        journal={EAI Endorsed Transactions on Internet of Things},
        volume={6},
        number={23},
        publisher={EAI},
        journal_a={IOT},
        year={2020},
        month={10},
        keywords={Aloha, distributed queuing, collision resolution, massive Machine-to-Machine (M2M) communications, random access protocol, tree splitting},
        doi={10.4108/eai.16-10-2020.166663}
    }
    
  • Romeo Nibitanga
    Elijah Mwangi
    Edward Ndung’u
    Year: 2020
    Statistical Analysis of a Distributed Queuing Random Access Protocol in a Massive Communication Environment
    IOT
    EAI
    DOI: 10.4108/eai.16-10-2020.166663
Romeo Nibitanga1,*, Elijah Mwangi2, Edward Ndung’u3
  • 1: Pan African University Institute of Basic Sciences, Technology and Innovation, Kenya
  • 2: University of Nairobi, Kenya
  • 3: Jomo Kenyatta University of Agriculture and Technology, Kenya
*Contact email: nibitanga.romeo@students.jkuat.ac.ke

Abstract

Most of the networks deployed for massive IoT communications use Aloha-based algorithms for channel access. However, those algorithms are known to be unstable and inefficient when the network size is high. Since recently, a Distributed Queuing (DQ) algorithm is being proposed as a solution to mitigate several of the Aloha issues in IoT networks. In this paper, a statistical performance analysis of the DQ algorithm without any prior consideration of any physical layer is presented. We evaluate the DQ algorithm in a massive communication environment and give the average values for these performance metrics: collision resolution time, access delay per sensor, channel throughput, number of attempts required by a sensor to complete the contention process, number of nodes contending per frame and the distribution of contention slots into idle, successful, and collided. The goal of this paper is to provide a statistical baseline performance evaluation of the DQ algorithm in general.