Incentive mechanism design via smart contract in blockchain-based edge-assisted crowdsensing

doi:10.1007/s11704-024-3542-1

Front. Comput. Sci.

2025, Vol. 19

Issue (3) : 193802 https://doi.org/10.1007/s11704-024-3542-1

Information Security

Incentive mechanism design via smart contract in blockchain-based edge-assisted crowdsensing

Chenhao YING^1,², Haiming JIN¹, Jie LI^1,², Xueming SI^1,², Yuan LUO^1,²(

)

¹. Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
². Shanghai Jiao Tong University (Wuxi) Blockchain Advanced Research Center, Wuxi 214101, China

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Abstract

Edge-assisted mobile crowdsensing (EMCS) has gained significant attention as a data collection paradigm. However, existing incentive mechanisms in EMCS systems rely on centralized platforms, making them impractical for the decentralized nature of EMCS systems. To address this limitation, we propose CHASER, an incentive mechanism designed for blockchain-based EMCS (BEMCS) systems. In fact, CHASER can attract more participants by satisfying the incentive requirements of budget balance, double-side truthfulness, double-side individual rationality and also high social welfare. Furthermore, the proposed BEMCS system with CHASER in smart contracts guarantees the data confidentiality by utilizing an asymmetric encryption scheme, and the anonymity of participants by applying the zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK). This also restrains the malicious behaviors of participants. Finally, most simulations show that the social welfare of CHASER is increased by approximately $42 %$ when compared with the state-of-the-art approaches. Moreover, CHASER achieves a competitive ratio of approximately 0.8 and high task completion rate of over 0.8 in large-scale systems. These findings highlight the robustness and desirable performance of CHASER as an incentive mechanism within the BEMCS system.

Keywords mobile crowdsensing edge computing blockchain smart contract incentive mechanism

Corresponding Author(s): Yuan LUO

About author: Li Liu and Yanqing Liu contributed equally to this work.

Issue Date: 22 April 2024

Cite this article:

Chenhao YING,Haiming JIN,Jie LI, et al. Incentive mechanism design via smart contract in blockchain-based edge-assisted crowdsensing[J]. Front. Comput. Sci., 2025, 19(3): 193802.

URL:

https://academic.hep.com.cn/fcs/EN/10.1007/s11704-024-3542-1
https://academic.hep.com.cn/fcs/EN/Y2025/V19/I3/193802

Fig.1 Framework of CHASER, where the numbers represent the order of events

Fig.2 (a) Anonymity authentication illustration of task publishing; (b) anonymity authentication illustration of parameter submission; (c) anonymity authentication illustration of data collection; (d) anonymity authentication illustration of payment transferring

Settings	Cost $c ?$ of worker	Value $v i$ of demander	Number $M$ of demanders	Number $W$ of workers	Ratio parameter $η$	Selection probability $?$
I	$[5, 20]$	$[15, 30]$	$[200, 380]$	$400$	$0.005$	$0.5$
II	$[5, 20]$	$[15, 30]$	$800$	$[300, 800]$	$0.003$	$0.5$
III	$[5, 30]$	$[10, 15], [12, 27], [15, 20]$	$350$	$[180, 360]$	$0.002$	$0.5$
IV	$[5, 10], [7, 12], [10, 15]$	$[5, 20]$	$[200, 560]$	$500$	$0.005$	$0.5$
V	$[5, 10]$	$[15, 20]$	$109$	$109$	$[10 ? 9, 10 ? 8]$	$4 η 6$
VI	$(0, 10]$	$(10, 20]$	$105, 106, 107, 108$	$105, 106, 107, 108$	$10 ? 5, 10 ? 6, 10 ? 7, 10 ? 8$	$[0.05, 0.185]$

Tab.1 Settings of parameter intervals for evaluating the performance of CHASER

Fig.3 (a) Gas cost of the smart contract versus different numbers of demander-worker pairs; (b) gas cost of the smart contract versus different sizes of transaction. The gas cost is paid for locking the transaction to the blockchain in Ethereum network

Fig.4 (a) Social welfare versus different numbers of demanders, where the number of workers is 400; (b) social welfare versus different numbers of workers, where the number of demanders is 800. The cost and value are sampled in [5,20] and [15,30], respectively

Fig.5 (a) Social welfare versus different numbers of workers, where the number of demanders is 350 and the cost is sampled in [5,30]; (b) social welfare achieved by CHASER versus different numbers of demanders, where the number of workers is 500 and the value is sampled in [5,20]

Fig.6 Competitive ratio on social welfare versus different values of ratio parameter η, where the theoretical analysis of the lower bound is calculated by the right hand of Eq. (16)

Fig.7 Task completion rate versus different values of ratio parameter

η

and selection probability

?

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