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Accepted author manuscript, 320 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Accepted author manuscript, 227 KB, PDF document
Available under license: CC BY-NC: Creative Commons Attribution-NonCommercial 4.0 International License
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - A Markovian Model for the Analysis of Age of Information in IoT Networks
AU - Abbas, Q.
AU - Hassan, S.A.
AU - Pervaiz, H.
AU - Ni, Q.
N1 - ©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.
PY - 2021/7/31
Y1 - 2021/7/31
N2 - 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
AB - 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
KW - age of information
KW - Agriculture
KW - Analytical models
KW - arrival rate
KW - Internet-of-thing
KW - Markov chain
KW - Markov processes
KW - Measurement
KW - Queueing analysis
KW - queuing theory.
KW - Real-time systems
KW - Uplink
KW - Markov chains
KW - Queueing theory
KW - Discrete time Markov chains
KW - Extensive simulations
KW - First in first outs
KW - Information packets
KW - Internet of Things (IOT)
KW - Markovian model
KW - Queue lengths
KW - Status updates
KW - Internet of things
U2 - 10.1109/LWC.2021.3075160
DO - 10.1109/LWC.2021.3075160
M3 - Journal article
VL - 10
SP - 1596
EP - 1600
JO - IEEE Wireless Communications Letters
JF - IEEE Wireless Communications Letters
SN - 2162-2337
IS - 7
ER -