边缘云环境下基于四方进化博弈的移动众包质量控制方法

IF 4.5 2区计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS

IEEE Transactions on Computational Social Systems Pub Date : 2024-02-06 DOI:10.1109/TCSS.2023.3338370

Ying Zhao;Yingjie Wang;Peiyong Duan;Haijing Zhang;Zhaowei Liu;Xiangrong Tong;Zhipeng Cai

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引用次数: 0

摘要

移动众包（MCS）是一种利用各种移动设备收集感知数据的新模式。移动边缘计算（MEC）可以有效利用移动边缘的设备资源，大大缓解网络带宽压力，提高响应速度。本文构建了一个由平台、人群工作者、任务请求者和边缘服务器组成的四方演化博弈模型。计算任务在边缘服务器上进行，大大降低了远程数据传输和网络运营成本，提高了服务质量。考虑到平台与工作者之间以及平台与请求者之间的勾结，我们利用复制器动力学方法分析了 MCS 中战略均衡的稳定性。我们得到了参与者在不同初始状态下的最优报酬策略。为了防止作弊和虚假报告问题，我们提供了奖惩策略。最后，通过模拟实验验证了四方演化博弈系统均衡的稳定性，并设计了激励策略以促使各方选择信任策略。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Mobile Crowdsourcing Quality Control Method Based on Four-Party Evolutionary Game in Edge Cloud Environment

Mobile crowdsourcing (MCS) is a new paradigm that uses various mobile devices to collect sensed data. Mobile edge computing (MEC) can effectively utilize the device resources of mobile edge, greatly relieve the pressure of network bandwidth and improve the response speed. In this article, we construct a four-party evolutionary game model consisting of the platform, crowd workers, task requesters, and edge servers. The computing tasks are conducted on edge servers, which greatly reduce remote data transmission and network operating costs and improve service quality. Taking into account the collusion between the platform and workers, and that between the platform and requesters, we analyze the stability of the strategic equilibrium in MCS using replicator dynamics methods. The optimal payoff strategies of the participants in different initial states are obtained. To prevent cheating and false-reporting problems, reward and punishment strategies are provided. Finally, the stability of the equilibrium of the four-party evolutionary game system is verified by simulation experiments, and an incentive strategy is designed to motivate all parties to choose the trust strategies.

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来源期刊

IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)

CiteScore

10.00

自引率

20.00%

发文量

316

期刊介绍： IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.