基于拍卖模型的移动群智感知网络激励机制

doi:10.11959/j.issn.1000-436x.2019138

通信学报 ›› 2019, Vol. 40 ›› Issue (7): 208-222.doi: 10.11959/j.issn.1000-436x.2019138

• 学术通信 • 上一篇

基于拍卖模型的移动群智感知网络激励机制

刘媛妮¹,李垚焬¹,李慧聪¹,李万林¹,张建辉²,赵国锋^1,³

¹ 重庆邮电大学通信与信息工程学院，重庆 400065
² 国家数字交换系统工程技术研究中心，河南郑州 450002
³ 重庆市高校光通信与网络重点实验室，重庆 400065

修回日期:2019-03-12 出版日期:2019-07-25 发布日期:2019-07-30
作者简介:刘媛妮（1982- ），女，河南邓州人，博士，重庆邮电大学副教授、硕士生导师，主要研究方向为移动群智感知、物联网安全、IP路由技术和复杂网络。|李垚焬（1995- ），男，重庆人，重庆邮电大学硕士生，主要研究方向为移动群智感知、物联网安全、IP路由技术和复杂网络。|李慧聪（1993- ），女，湖北松滋人，重庆邮电大学硕士生，主要研究方向为移动群智感知、物联网安全、IP路由技术和复杂网络。|李万林（1963- ），男，四川广安人，博士，重庆邮电大学教授、博士生导师，主要研究方向为移动大数据信息处理。|张建辉（1977- ），男，河南平顶山人，博士，国家数字交换系统工程技术研究中心副教授，主要研究方向为路由和交换设计、路由协议、资源调度、网络安全和未来网络。|赵国锋（1972- ），男，陕西泾阳人，博士，重庆邮电大学教授，主要研究方向为未来互联网、移动互联网、网络管理和网络安全。
基金资助:
国家自然科学基金资助项目(61501075);国家留学基金委项目(201707845004);“十三五”装备预研国防科技重点实验室基金资助项目(61422090301);重庆市教委科学技术研究基金资助项目(KJQN201800633);重庆市基础与前沿基金资助项目(2015jcyjBX0009)

Incentive mechanism based on auction model for mobile crowd sensing network

Yuanni LIU¹,Yaoxi LI¹,Huicong LI¹,Wanlin LI¹,Jianhui ZHANG²,Guofeng ZHAO^1,³

¹ School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China
² National Digital Switching System Engineering and Technological Research and Department Center,Zhengzhou 450002,China
³ Key Laboratory of Optical Communication and Network of Colleges and Universities in Chongqing,Chongqing 400065,China

Revised:2019-03-12 Online:2019-07-25 Published:2019-07-30
Supported by:
The National Natural Science Foundation of China(61501075);China Scholarship Council Project(201707845004);Foundation of Key Laboratory in National Defense Science and Technology for Equipment Pre-Research in the 13th Five-Year Plan(61422090301);Science and Technology Research Program of Chongqing Municipal Education Commission(KJQN201800633);The Chongqing Municipal Project Under Grant CSTC(2015jcyjBX0009)

摘要/Abstract

摘要：

移动群智感知网络中用户的自私性和不确定性会造成用户参与感知活动的积极性不高及任务完成率较低等问题。针对此问题，提出了一种基于拍卖模型的激励机制。首先，以最大化用户效用为目标，在所提出的逆向拍卖机制（IMRA）中，以任务为中心进行赢标者选择且基于临界价格对赢标者进行报酬支付。然后，利用双向交互的激励机制（UBIM）使临时退出的用户可将未完成的任务转售给新用户，并提出基于二部图的用户匹配算法。实验结果表明，与TRAC、IMC-SS机制相比，所提的IMRA具有更高的用户平均效用和任务覆盖率，使用UBIM后也提高了任务完成率。

关键词: 移动群智感知, 激励机制, 逆向拍卖, 双向拍卖

Abstract:

The selfishness and uncertainty of user behaviors in the mobile crowd sensing network make them unwilling to participate in sensing activities,which may result to a lower sensing task completion rate.To deal with these problems,an incentive mechanism based on auction model was proposed.In order to maximize the utility of each user,the proposed incentive method based on reverse auction (IMRA) leveraged a task-centric method to choose winners,and payed them according to a critical-price strategy.Furthermore,the proposed user-bidirectional interaction incentive mechanism (UBIM) helped drop-out users (buyers) to transfer their unfinished tasks to new users.Simulation results show that,compared with TRAC and IMC-SS,IMRA can achieve a better performance in terms of average user utility and tasks coverage ratio,and the task completion ratio can also be improved by UBIM.

Key words: mobile crowd sensing, incentive mechanism, reverse auction, double auction

中图分类号:

TP393

刘媛妮,李垚焬,李慧聪,李万林,张建辉,赵国锋. 基于拍卖模型的移动群智感知网络激励机制[J]. 通信学报, 2019, 40(7): 208-222.

Yuanni LIU,Yaoxi LI,Huicong LI,Wanlin LI,Jianhui ZHANG,Guofeng ZHAO. Incentive mechanism based on auction model for mobile crowd sensing network[J]. Journal on Communications, 2019, 40(7): 208-222.

图/表 13

图1

图2

表1

本文所用符号及其含义"

符号标识	说明
U，n，u_i	用户集，总用户数，单个用户
Γ，m，τ_x	任务集，总任务数，单个任务x
s _x，d_x	任务τ_x开始时间，任务τ_x截止时间
t _x，Δt_x	完成任务τ_x所需时间，用户执行任务τ_x的时间
V，V_x	任务价值集合，任务τ_x的价值
Γ _i，v_x	用户u_i上报的任务集，任务集Γ_i中任务的总价值
b_i	用户u_i的竞价
c_i	用户u_i对应于竞价b_i的感知成本
p_i	对用户u_i的支付
S	赢标用户集合
$T_{τ_{i}}$	任务奖励
$U^{b} / u_{i}^{b}, U^{s} / u_{j}^{s}$	买方用户集/买方用户，卖方用户集/卖方用户
B (t)/S(t)	在周期t内到达的买方/卖方用户集
B ^W(t)	在周期t内与卖方匹配成功的买方用户集
S ^W(t)	在周期t内赢得任务的卖方用户集
$\| B (t) \| / \| S (t) \|$	用户集B(t)/S(t)中的用户数量

表1

图3

表2

表3

图4

图5

图6

图7

图8

图9

图10

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名称	参数值
用户数n	50,500]，以50为步长
总任务数m	10,100]，以10为步长
用户竞价b_i	服从[5,10]均匀分布
感知任务成本c_i	服从[1,5]均匀分布
任务的价值V_i	服从[1,50]均匀分布
中途退出的用户数占总用户数的比例p	0.2

名称	参数
买卖双方报价范围	(0,5]均匀分布
买方用户数目α	{10,20,30,40,50}
卖方用户数目β	{10,20,30,40,50,60,70,80,90,100}
拍卖总周期T	100
最大等待耐心I	{0,3 ,6 ,9 ,12,15,18,21,24,27,30}
到达率λ	{1,2,3,4,5,6,7,8,9,10}

基于拍卖模型的移动群智感知网络激励机制

Incentive mechanism based on auction model for mobile crowd sensing network

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参考文献 33

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