Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling

Zhengru Fang; Jingjing Wang; Chunxiao Jiang; Xijun Wang; Yong Ren

doi:10.1109/TVT.2022.3176819

Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling

Zhengru Fang
, Jingjing Wang^*
, Chunxiao Jiang
, Xijun Wang
, Yong Ren

^*Corresponding author for this work

School of Cyber Science and Technology

Research output: Contribution to journal › Article › peer-review

36 Scopus citations

Abstract

We investigate the peak age of information (PAoI) in underwater wireless sensor networks (UWSNs), where Internet of underwater things (IoUT) nodes transmit the latest packets to the sink node, which is in charge of adjusting the sleep-scheduling to match network demands. In order to reduce PAoI, we propose active queue management (AQM) policy of the IoUT node, beneficially compresses the packets having large waiting time. Moreover, we deduce the closed-form expressions of the average PAoI as well as the energy cost relying on probability generating function and matrix-geometric solutions. Numerical results verify that the IoUT node relying on the AQM policy has a lower PAoI and energy cost in comparison to those using non-AQM policy.

Original language	English
Pages (from-to)	10132-10136
Number of pages	5
Journal	IEEE Transactions on Vehicular Technology
Volume	71
Issue number	9
DOIs	https://doi.org/10.1109/TVT.2022.3176819
State	Published - 1 Sep 2022

Keywords

Active queue management
age of information
multiple vacation queueing model
underwater wireless sensor networks

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10.1109/TVT.2022.3176819

Cite this

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title = "Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling",

abstract = "We investigate the peak age of information (PAoI) in underwater wireless sensor networks (UWSNs), where Internet of underwater things (IoUT) nodes transmit the latest packets to the sink node, which is in charge of adjusting the sleep-scheduling to match network demands. In order to reduce PAoI, we propose active queue management (AQM) policy of the IoUT node, beneficially compresses the packets having large waiting time. Moreover, we deduce the closed-form expressions of the average PAoI as well as the energy cost relying on probability generating function and matrix-geometric solutions. Numerical results verify that the IoUT node relying on the AQM policy has a lower PAoI and energy cost in comparison to those using non-AQM policy.",

keywords = "Active queue management, age of information, multiple vacation queueing model, underwater wireless sensor networks",

author = "Zhengru Fang and Jingjing Wang and Chunxiao Jiang and Xijun Wang and Yong Ren",

note = "Publisher Copyright: {\textcopyright} 1967-2012 IEEE.",

year = "2022",

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doi = "10.1109/TVT.2022.3176819",

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T1 - Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling

AU - Fang, Zhengru

AU - Wang, Jingjing

AU - Jiang, Chunxiao

AU - Wang, Xijun

AU - Ren, Yong

PY - 2022/9/1

Y1 - 2022/9/1

N2 - We investigate the peak age of information (PAoI) in underwater wireless sensor networks (UWSNs), where Internet of underwater things (IoUT) nodes transmit the latest packets to the sink node, which is in charge of adjusting the sleep-scheduling to match network demands. In order to reduce PAoI, we propose active queue management (AQM) policy of the IoUT node, beneficially compresses the packets having large waiting time. Moreover, we deduce the closed-form expressions of the average PAoI as well as the energy cost relying on probability generating function and matrix-geometric solutions. Numerical results verify that the IoUT node relying on the AQM policy has a lower PAoI and energy cost in comparison to those using non-AQM policy.

AB - We investigate the peak age of information (PAoI) in underwater wireless sensor networks (UWSNs), where Internet of underwater things (IoUT) nodes transmit the latest packets to the sink node, which is in charge of adjusting the sleep-scheduling to match network demands. In order to reduce PAoI, we propose active queue management (AQM) policy of the IoUT node, beneficially compresses the packets having large waiting time. Moreover, we deduce the closed-form expressions of the average PAoI as well as the energy cost relying on probability generating function and matrix-geometric solutions. Numerical results verify that the IoUT node relying on the AQM policy has a lower PAoI and energy cost in comparison to those using non-AQM policy.

KW - Active queue management

KW - age of information

KW - multiple vacation queueing model

KW - underwater wireless sensor networks

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DO - 10.1109/TVT.2022.3176819

M3 - 文章

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SN - 0018-9545

VL - 71

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EP - 10136

JO - IEEE Transactions on Vehicular Technology

JF - IEEE Transactions on Vehicular Technology

IS - 9

ER -

Average Peak Age of Information in Underwater Information Collection With Sleep-Scheduling

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Keywords

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