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Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting

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Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting. / Hu, Jiejun; Yang, Kun; Hu, Liang et al.
In: IEEE Access, Vol. 6, 25.07.2018, p. 37604-37614.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Hu J, Yang K, Hu L, Wang K. Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting. IEEE Access. 2018 Jul 25;6:37604-37614. Epub 2018 May 22. doi: 10.1109/ACCESS.2018.2839582

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Hu, Jiejun ; Yang, Kun ; Hu, Liang et al. / Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting. In: IEEE Access. 2018 ; Vol. 6. pp. 37604-37614.

Bibtex

@article{b1a22a77ec6b4d51bf9a79ca989a93c3,
title = "Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting",
abstract = "Mobile crowdsensing (MCS) is a new sensing framework that empowers normal mobile devices to participate in sensing tasks. The key challenge that degrades the performance of MCS is selfish mobile users who conserve the resources (e.g., CPU, battery, and bandwidth) of their devices. Thus, we introduce energy harvesting (EH) as rewards into MCS, and thus provide more possibilities to improve the quality of service (QoS) of the system. In this paper, we propose a game theoretic approach for achieving sustainable and higher quality sensing task execution in MCS. The proposed solution is implemented as a two-stage game. The first stage of the game is the system reward game, in which the system is the leader, who allocates the task and reward, and the mobile devices are the followers who execute the tasks. The second stage of the game is called the participant decision-making game, in which we consider both the network channel condition and participant{\textquoteright}s abilities. We analyze the features of the second stage of the game and show that the game admits a Nash equilibrium (NE). Based on the NE of the second stage of the game, the system can admit a Stackelberg equilibrium, at which the utility is maximized. Simulation results demonstrate that the proposed mechanism can achieve a better QoS and prolong the system lifetime while also providing a proper incentive mechanism for MCS.",
author = "Jiejun Hu and Kun Yang and Liang Hu and Kezhi Wang",
year = "2018",
month = jul,
day = "25",
doi = "10.1109/ACCESS.2018.2839582",
language = "English",
volume = "6",
pages = "37604--37614",
journal = "IEEE Access",
issn = "2169-3536",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

RIS

TY - JOUR

T1 - Reward-Aided Sensing Task Execution in Mobile Crowdsensing Enabled by Energy Harvesting

AU - Hu, Jiejun

AU - Yang, Kun

AU - Hu, Liang

AU - Wang, Kezhi

PY - 2018/7/25

Y1 - 2018/7/25

N2 - Mobile crowdsensing (MCS) is a new sensing framework that empowers normal mobile devices to participate in sensing tasks. The key challenge that degrades the performance of MCS is selfish mobile users who conserve the resources (e.g., CPU, battery, and bandwidth) of their devices. Thus, we introduce energy harvesting (EH) as rewards into MCS, and thus provide more possibilities to improve the quality of service (QoS) of the system. In this paper, we propose a game theoretic approach for achieving sustainable and higher quality sensing task execution in MCS. The proposed solution is implemented as a two-stage game. The first stage of the game is the system reward game, in which the system is the leader, who allocates the task and reward, and the mobile devices are the followers who execute the tasks. The second stage of the game is called the participant decision-making game, in which we consider both the network channel condition and participant’s abilities. We analyze the features of the second stage of the game and show that the game admits a Nash equilibrium (NE). Based on the NE of the second stage of the game, the system can admit a Stackelberg equilibrium, at which the utility is maximized. Simulation results demonstrate that the proposed mechanism can achieve a better QoS and prolong the system lifetime while also providing a proper incentive mechanism for MCS.

AB - Mobile crowdsensing (MCS) is a new sensing framework that empowers normal mobile devices to participate in sensing tasks. The key challenge that degrades the performance of MCS is selfish mobile users who conserve the resources (e.g., CPU, battery, and bandwidth) of their devices. Thus, we introduce energy harvesting (EH) as rewards into MCS, and thus provide more possibilities to improve the quality of service (QoS) of the system. In this paper, we propose a game theoretic approach for achieving sustainable and higher quality sensing task execution in MCS. The proposed solution is implemented as a two-stage game. The first stage of the game is the system reward game, in which the system is the leader, who allocates the task and reward, and the mobile devices are the followers who execute the tasks. The second stage of the game is called the participant decision-making game, in which we consider both the network channel condition and participant’s abilities. We analyze the features of the second stage of the game and show that the game admits a Nash equilibrium (NE). Based on the NE of the second stage of the game, the system can admit a Stackelberg equilibrium, at which the utility is maximized. Simulation results demonstrate that the proposed mechanism can achieve a better QoS and prolong the system lifetime while also providing a proper incentive mechanism for MCS.

U2 - 10.1109/ACCESS.2018.2839582

DO - 10.1109/ACCESS.2018.2839582

M3 - Journal article

VL - 6

SP - 37604

EP - 37614

JO - IEEE Access

JF - IEEE Access

SN - 2169-3536

ER -