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A Markovian Model for the Analysis of Age of Information in IoT Networks

Research output: Contribution to journalJournal articlepeer-review

E-pub ahead of print
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<mark>Journal publication date</mark>22/04/2021
<mark>Journal</mark>IEEE Wireless Communications Letters
Number of pages5
Publication StatusE-pub ahead of print
Early online date22/04/21
<mark>Original language</mark>English

Abstract

Age of Information (AoI) is a critical metric in status update systems as these systems require the fresh updates. This paper investigates the uplink of an Internet-of-thing (IoT) network where L nodes transmit their information packets to a base station. The effects of the arrival rate of packets at the nodes, the number of nodes in the system, and queue length of each node have been studied by devising a discrete time Markov chain (MC) model. This model helps in predicting the values of AoI and probability of packet drops in such systems. The notion of first-in first-out is used for queuing, which transmits the oldest packet first, resulting in decreasing the overall AoI of the system. The results show that AoI increases with the increase in queue length, number of nodes and arrival rate and we quantify the aforementioned metrics using the MC model.The results found using the MC model are also validated using extensive simulations. IEEE

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©2021 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.