In a blockchain-based system, the lack of centralized control requires active participation and cooperative behaviors of system entities to ensure system security and sustainability. However, dynamic environments and unpredictable entity behaviors challenge the performances of such systems in practice. Therefore, designing a feasible incentive mechanism to regulate entity behaviors becomes essential to improve blockchain system performance. The prosperous characteristics of blockchain can also contribute to an effective incentive mechanism. Unfortunately, current literature still lacks a thorough survey on incentive mechanisms related to the blockchain to understand how incentive mechanisms and blockchain make each other better. To this end, we propose evaluation requirements in terms of the properties and costs of incentive mechanisms. On one hand, we provide a taxonomy of the incentive mechanisms of blockchain systems according to blockchain versions, incentive forms and incentive goals. On the other hand, we categorize blockchain-based incentive mechanisms according to application scenarios and incentive goals. During the review, we discuss the advantages and disadvantages of state-of-art incentive mechanisms based on the proposed evaluation requirements. Through careful review, we present how incentive mechanisms and blockchain benefit with each other, discover a number of unresolved issues, and point out corresponding potential directions for future research.
Decentralized crowdsourcing removes the dependence on a trusted centralized platform based on blockchain and ensures system stability through the consensus of miners. The lack of centralized supervision requires all kinds of system nodes to voluntarily participate while their behaviors are profitdriven and unpredictable, thus introducing challenges to system performance. Moreover, the nodes in a decentralized crowdsourcing system inherently observe little information about the system status; therefore, it is difficult for them to discover and adopt theoretically optimal strategies. Current literature still lacks an effective mechanism to motivate the participation of all types of nodes. To this end, this paper employs a two-layer game model to simulate the interactions in the decentralized crowdsourcing system for investigating the participation willingness of different system nodes. Specifically, we apply a Stackelberg game to model the interactions of a crowdsourcing requester and other nodes, where the requester decides its reward policy and the others respond by selecting their roles to play. In addition, the interaction of the bounded rational other nodes is further represented as an evolutionary game. After analyzing the game model, we further design an incentive mechanism to maximize the requester utility while motivating other nodes to actively participate in the crowdsourcing. Through experimental simulations, we verify the effectiveness of the proposed incentive mechanism.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.