计算机科学 ›› 2022, Vol. 49 ›› Issue (9): 275-282.doi: 10.11896/jsjkx.210700129
傅彦铭1, 朱杰夫1, 蒋侃2, 黄保华1, 孟庆文1, 周兴1
FU Yan-ming1, ZHU Jie-fu1, JIANG Kan2, HUANG Bao-hua1, MENG Qing-wen1, ZHOU Xing1
摘要： 随着移动众包的快速发展,市面上的众包平台如雨后春笋般出现,它们发布任务并利用人群的力量来执行任务、收集数据。此时,移动众包中有效的激励机制变得十分重要。然而现有的激励机制只片面地考虑工人的信誉度、所在位置和执行时间等,这使得众包平台在有限的预算或其他约束的情况下选定优质工人并分配多个任务变得困难。针对以上问题,文中提出了一种基于多约束工人择优的激励机制(Multi-constrained Worker Selection Incentive Mechanism,MSIM),该模型依赖于两个相关算法:一是基于改进逆向拍卖的工人择优算法,该算法综合考虑工人信誉度、地理位置、任务完成度、结果质量等多个重要约束来选择最优的工人执行任务;二是评估和奖惩算法,该算法对任务执行结果和工人信誉度进行评估,从而制定对工人的奖励与惩罚规则。实验结果表明,MSIM可以选出优秀的工人,并提高任务执行结果的可信度和工人信誉度,是一种良好的激励机制。
中图分类号:
| [1]WU Y,ZENG J R,PENG H,et al.Survey on incentive mechanisms for crowd sensing[J].Journal of Software,2016,27(8):2025-2047. [2]HU Y,WANG Y J,TONG X R.Task Recommendation ModelBased on Crowd Worker's Movement Trajectory[J].Computer Science,2020,47(10):32-40. [3]WANG Y,CAI Z,TONG X,et al.Truthful incentive mechanismwith location privacy-preserving for mobile crowdsourcing systems [J].Computer Networks,2018,135:32-43. [4]LI Z,CHENG B,GAO X,et al.A unified task recommendation strategy for realistic mobile crowdsourcing system[J].Theoretical Computer Science,2021,857(D):43-58. [5]JIANG N,XU D,ZHOU J,et al.Toward optimal participant decisions with voting-based incentive model for crowd sensing[J].Information Sciences,2020,512:1-17. [6]JIA X,ZHENG Q R,LI J X,et al.Incentive Mechanism for Multiple Cooperative Tasks with Compatible Users in Mobile Crowd Sensing via Online Communities[J].IEEE Transactions on Mobile Computing,2020,19(7):1618-1633. [7]JIANG L Y,FAN H,HU W,et al.Quality-Aware IncentiveMechanism for Mobile Crowd Sensing[J].Journal of Sensors,2017(3):1-14. [8]CAI H,ZHU Y,FENG Z,et al.Truthful incentive mechanisms for mobile crowd sensing with dynamic smartphones[J].Computer Networks,2018,141:1-16. [9]CHEN X,MIN L,ZHOU Y,et al.A Truthful Incentive Mechanism for Online Recruitment in Mobile Crowd Sensing System[J].Sensors (Basel,Switzerland),2017,17(1):1-17. [10]LI X H,ZHU Q.Social Incentive Mechanism Based Multi-User Sensing Time Optimization in Co-Operative Spectrum Sensing with Mobile Crowd Sensing[J].Sensors,2018,18(1):1-21. [11]YANG G,HE S B,SHI Z G,et al.Promoting Cooperation by the Social Incentive Mechanism in Mobile Crowdsensing[J].IEEE Communications Magazine,2017,55(3):86-92. [12]AMINTOOSI H,KANHERE S S,TORSHIZ M N.A socially-aware incentive scheme for social participatory sensing[C]//2015 IEEE 10th International Conference on Intelligent Sensors,Sensor Networks and Information Processing,ISSNIP 2015.Institute of Electrical and Electronics Engineers Inc.,2015:1-6. [13]LUO T,KANHERE S S,TAN H P.SEWing a Simple Endorsement Web to Incentivize Trustworthy Participatory Sensing[C]//Eleventh IEEE International Conference on Sensing.IEEE,2014:636-644. [14]ROUGHGARDEN T.Stackelberg scheduling strategies[J].Siam Journal on Computing,2001,33(2):332-350. [15]MYERSON R B.Optimal auciton design[J].Mathematics ofOperations Research,1981,6(1):58-73. [16]YANG D,XUE G,XI F,et al.Crowdsourcing to smartphones:Incentive mechanism design for mobile phone sensing[C]//Proceedings of the Annual International Conference on Mobile Computing and Networking.MOBICOM,2012:173-184. [17]EMILIANI M L,STEC D J.Online reverse auction purchasing contracts[J].Supply Chain Management,2001,6(3):101-105. [18]AHMED A,PATEL A,BROWN T,et al.Task assignment for a physical agent team via a dynamic forward/reverse auction mechanism[C]//International Conference on Integration of Knowledge Intensive Multi-Agent Systems,2005.2005:311-317. [19]LEE J S,HOH B.Sell your experiences:a market mechanism based incentive for participatory sensing[C]//2010 IEEE International Conference on Pervasive Computing and Communications(PerCom 2010).IEEE,2010:60-68. [20]ZHANG X,XUE G,YU R,et al.Robust Incentive Tree Design for Mobile Crowdsensing[C]//2017 IEEE 37th International Conference on Distributed Computing Systems(ICDCS).IEEE,2017:458-468. [21]YANG T,LI Z Q,YANG L X.Reputation-Updating Online Incentive Mechanism for Mobile Crowd Sensing [J].Journal of Data Acquisition and Processing,2019,34(5):797-807. [22]JIN H,SU L,CHEN D,et al.Quality of information aware incentive mechanisms for mobile crowd sensing systems[C]//Proceedings of the International Symposium on Mobile Ad Hoc Networking and Computing(MobiHoc).Association for Computing Machinery,2015:167-176. [23]HE S B,SHIN D H,ZHANG J S,et al.Near-Optimal Allocation Algorithms for Location-Dependent Tasks in Crowdsensing[J].IEEE Transactions on Vehicular Technology,2017,66(4):3392-3405. [24]XIAO M J,WU J,HUANG H,et al.Deadline-sensitive UserRecruitment for mobile crowdsensing with probabilistic collaboration[C]//IEEE International Conference on Network Protocols.IEEE Computer Society,2016. [25]ZHAO D,LI X Y,MA H.How to crowdsource tasks truthfully without sacrificing utility:Online incentive mechanisms with budget constraint[C]//IEEE INFOCOM 2014-IEEE Confe-rence on Computer Communications.Toronto,Canada:IEEE,2014:1213-1221. [26]ZHAO D,LI X Y,MA H.Budgetfeasible online incentivemecha-nisms for crowdsourcing tasks truthfully[J].IEEE/ACM Transactions on Networking,2016,24(2):647-661. [27]ZHOU P,ZHENG Y,LI M,How Long to Wait?Predicting Bus Arrival Time With Mobile Phone Based Participatory Sensing[J].Mobile Computing,2014,13(6):1228-1241. |
| [1] | 王思明, 谭北海, 余荣. 面向6G可信可靠智能的区块链分片与激励机制 Blockchain Sharding and Incentive Mechanism for 6G Dependable Intelligence 计算机科学, 2022, 49(6): 32-38. https://doi.org/10.11896/jsjkx.220400004 |
| [2] | 杨昕宇, 彭长根, 杨辉, 丁红发. 基于演化博弈的理性拜占庭容错共识算法 Rational PBFT Consensus Algorithm with Evolutionary Game 计算机科学, 2022, 49(3): 360-370. https://doi.org/10.11896/jsjkx.210900110 |
| [3] | 杜辉, 李卓, 陈昕. 基于在线双边拍卖的分层联邦学习激励机制 Incentive Mechanism for Hierarchical Federated Learning Based on Online Double Auction 计算机科学, 2022, 49(3): 23-30. https://doi.org/10.11896/jsjkx.210800051 |
| [4] | 王鑫, 周泽宝, 余芸, 陈禹旭, 任昊文, 蒋一波, 孙凌云. 一种面向电能量数据的联邦学习可靠性激励机制 Reliable Incentive Mechanism for Federated Learning of Electric Metering Data 计算机科学, 2022, 49(3): 31-38. https://doi.org/10.11896/jsjkx.210700195 |
| [5] | 周秋艳, 肖满生, 张龙信, 张晓丽, 杨文理. 多约束条件下生产排程智能优化技术 Intelligent Optimization Technology of Production Scheduling Under Multiple Constraints 计算机科学, 2021, 48(3): 239-245. https://doi.org/10.11896/jsjkx.200300105 |
| [6] | 胡颖, 王莹洁, 童向荣. 基于众包工人移动轨迹的任务推荐模型 Task Recommendation Model Based on Crowd Worker’s Movement Trajectory 计算机科学, 2020, 47(10): 32-40. https://doi.org/10.11896/jsjkx.200600180 |
| [7] | 童海,白光伟,沈航. 基于双向拍卖的k-匿名激励机制 Double-auction-based Incentive Mechanism for k-anonymity 计算机科学, 2019, 46(3): 202-208. https://doi.org/10.11896/j.issn.1002-137X.2019.03.030 |
| [8] | 张凤荔,周洪川,张俊娇,刘渊,张春瑞. 零知识下的比特流未知协议分类模型 Unknown Bit-stream Protocol Classification Model with Zero-knowledge 计算机科学, 2016, 43(8): 39-44. https://doi.org/10.11896/j.issn.1002-137X.2016.08.008 |
| [9] | 蒲国林,邱玉辉. 基于本体的多约束服务发现 Multi-constraints Service Discovery Based on Ontology 计算机科学, 2015, 42(5): 200-203. https://doi.org/10.11896/j.issn.1002-137X.2015.05.040 |
| [10] | 廖新考,王力生. 基于社会规范准则和联合抵制的节点激励机制研究 Research on Incentive Mechanism Based on Social Norms and Boycott 计算机科学, 2014, 41(4): 28-30. |
| [11] | 杨双双，郭玉翠，左赛哲，胡映然. 基于资源评价的信任管理模型 Trust Management Model Based on Evaluation of Resources 计算机科学, 2012, 39(8): 31-. |
| [12] | 王浩云 徐焕良 任守纲 张晨. 基于第二价拍卖理论的P2P网络组播节点激励机制研究 Incentive Mechanisms for Multicast Nodes Based on Second-price Auction Theory in P2P Network 计算机科学, 2012, 39(11): 41-44. |
| [13] | 江敏，皮德常，孙兰. 一种多约束的密度聚类算法的研究 Research on Density Clustering Algorithm with a Multiple Constraints 计算机科学, 2011, 38(Z10): 143-145. |
| [14] | 胡建理,吴泉源,周斌. 基于信任的P2P拓扑进化机制 Effective Trust-based Topology Evolution Mechanism for P2P Networks 计算机科学, 2010, 37(1): 95-98. |
| [15] | 冯健 房鼎益 陈晓江. P2P流媒体激励机制研究 计算机科学, 2008, 35(5): 29-31. |
|
||
首页