Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications

Mehmet Ariman; Lal Verda Cakir; Mehmet Ozdem; Berk Canberk

doi:10.1109/SmartNets58706.2023.10215658

Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications

Mehmet Ariman^*, Lal Verda Cakir, Mehmet Ozdem, Berk Canberk

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms.

Original language	English
Title of host publication	2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798350302523
DOIs	https://doi.org/10.1109/SmartNets58706.2023.10215658
Publication status	Published - 2023
Externally published	Yes
Event	2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023 - Istanbul, Turkey Duration: 25 Jul 2023 → 27 Jul 2023

Publication series

Name	2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

Conference

Conference	2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023
Country/Territory	Turkey
City	Istanbul
Period	25/07/23 → 27/07/23

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Keywords

Ad-Hoc
Deep Q-Learning
Machine Learning
Resource Allocation
Traffic Engineering
UAV Network

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1109/SmartNets58706.2023.10215658

Cite this

Ariman, M., Cakir, L. V., Ozdem, M., & Canberk, B. (2023). Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. In 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023 (2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SmartNets58706.2023.10215658

Ariman, Mehmet ; Cakir, Lal Verda ; Ozdem, Mehmet et al. / Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023).

@inproceedings{f4e06d18c38b42378527cd31ec14b674,

title = "Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications",

abstract = "Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9\%, performing 91\% accuracy, compared to the trivial channel scoring-based selection algorithms.",

keywords = "Ad-Hoc, Deep Q-Learning, Machine Learning, Resource Allocation, Traffic Engineering, UAV Network",

author = "Mehmet Ariman and Cakir, \{Lal Verda\} and Mehmet Ozdem and Berk Canberk",

note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023 ; Conference date: 25-07-2023 Through 27-07-2023",

year = "2023",

doi = "10.1109/SmartNets58706.2023.10215658",

language = "English",

series = "2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023",

address = "United States",

}

Ariman, M, Cakir, LV, Ozdem, M & Canberk, B 2023, Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. in 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023. 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023, Institute of Electrical and Electronics Engineers Inc., 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023, Istanbul, Turkey, 25/07/23. https://doi.org/10.1109/SmartNets58706.2023.10215658

Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. / Ariman, Mehmet; Cakir, Lal Verda; Ozdem, Mehmet et al.
2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023. Institute of Electrical and Electronics Engineers Inc., 2023. (2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications

AU - Ariman, Mehmet

AU - Cakir, Lal Verda

AU - Ozdem, Mehmet

AU - Canberk, Berk

PY - 2023

Y1 - 2023

N2 - Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms.

AB - Unmanned air vehicles are becoming widespread, driven by improved wireless technologies. However, the WiFi technology used for communication has a highly crowded and unevenly distributed channel occupancy in its spectrum. To overcome this, WiFi resources need to be utilized efficiently. Therefore, this paper proposes the Opportunistic Reinforcement Learning-based WiFi Access scheme, which exploits intermittent channel occupancy to solve the NP-hard channel assignment problem. As a result, the proposed model has improved the accurate channel selection on the UAVs by 9%, performing 91% accuracy, compared to the trivial channel scoring-based selection algorithms.

KW - Ad-Hoc

KW - Deep Q-Learning

KW - Machine Learning

KW - Resource Allocation

KW - Traffic Engineering

KW - UAV Network

UR - https://www.scopus.com/pages/publications/85170637102

U2 - 10.1109/SmartNets58706.2023.10215658

DO - 10.1109/SmartNets58706.2023.10215658

M3 - Conference contribution

AN - SCOPUS:85170637102

T3 - 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

BT - 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023

Y2 - 25 July 2023 through 27 July 2023

ER -

Ariman M, Cakir LV, Ozdem M, Canberk B. Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications. In 2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023. Institute of Electrical and Electronics Engineers Inc. 2023. (2023 International Conference on Smart Applications, Communications and Networking, SmartNets 2023). doi: 10.1109/SmartNets58706.2023.10215658

Opportunistic RL-based WiFi Access for Aerial Sensor Nodes in Smart City Applications

Abstract

Publication series

Conference

Bibliographical note

Keywords

UN SDGs

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