A Secure Task Allocation Technology Based on Crowd Sensing Network

doi:10.3969/j.issn.1000-3428.2016.06.028

Abstract

Abstract: Crowd sensing networks achieve large-scale sensing by using the existing sensing equipment of users as well as the deployed communication networks.Hence,it can efficiently address the critical problem of high cost of large scale network.However,during the process of task transfer and allocation for mobile users,group collusion as well as task copy and forwarding may cause serious threats for specific users.Aiming at this problem,based on crowd sensing network,this paper proposes a secure task distribution technique,whose main idea is to apply d-choice method in balls-into-bins theory into task allocation process and achieve load balancing for all users while the established threshold strategy ensures the security of user tasks.Simulation results show that,compared with the random task allocation technology,the proposed technology is able to balance the task load more efficiently,thus ensuring task safety.

Key words: crowd sensing, mobile computing, secure task allocation technology, balls-into-bins theory, Distributed Sensing Network(DSN)

摘要： 群智感知网络利用广大用户现有的感知设备和已部署的通信网络可实现大规模的感知,能够解决当前大规模感知网络成本较高的问题。然而移动用户在任务传输和分配过程中,群体合谋以及任务拷贝转发都会对特定用户任务的安全造成威胁。针对这一问题,基于群智感知网络,提出一种任务安全分发技术,通过将球箱理论中的d-choice方法应用到任务分配过程中,在实现全体用户负载均衡的同时,根据制定的阈值策略,保证用户任务的安全性。仿真结果表明,相比随机任务分配技术,所提出的技术能够更有效地均衡任务负载,从而保证任务安全。

关键词: 群智感知, 移动计算, 任务安全分发技术, 球箱理论, 分布式传感网络

CLC Number:

TP393

TANG Yan,LIU Ruiqi,YANG Panlong,FAN Xiaochen,LI Qingyu. A Secure Task Allocation Technology Based on Crowd Sensing Network[J]. Computer Engineering, doi: 10.3969/j.issn.1000-3428.2016.06.028.

唐艳,刘瑞琪,杨盘隆,范晓宸,李晴瑜. 一种基于群智感知网络的任务安全分发技术[J]. 计算机工程, doi: 10.3969/j.issn.1000-3428.2016.06.028.

/ / Recommend / Download Citations

URL: http://www.ecice06.com/EN/10.3969/j.issn.1000-3428.2016.06.028

http://www.ecice06.com/EN/Y2016/V42/I6/161

References

参考文献［1］刘云浩.群智感知计算［J］.中国计算机学会通讯,2012,8(10):38-41. ［2］Bernstein M S,Brandt J,Miller R C,et al.Crowds in Two Seconds:Enabling Real-time Crowd-powered Interfaces［C］//Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology.New York,USA:ACM Press,2011:33- 42. ［3］Chon Y,Lane N D,Li Fan,et al.Automatically Characterizing Places with Opportunistic Crowdsensing Using Smartphones［C］//Proceedings of ACM Conference on Ubiquitous Computing.New York,USA:ACM Press,2012:481-490. ［4］Zhang Daqing,Xiong Haoyi,Wang Leye,et al.Crowd Recruiter:Selecting Participants for Piggyback Crowdsensing Under Probabilistic Coverage Con-straint［C］//Proceedings of ACM International Joint Conference on Pervasive and Ubiquitous Computing.New York,USA:ACM Press,2014:703-714. ［5］Luo Tie,Kanhere S S,Tan Hwee-pink.Sewing a Simple Endorsement Web to Incentivize Trustworthy Par-ticipatory Sensing［C］//Proceedings of the 11th Annual IEEE International Conference on Sensing,Communica-tion,and Networking.Washington D.C.,USA:IEEE Press,2014:636-644. ［6］Mitzenmacher M,Richa A W,Sitaraman R.The Power of Two Random Choices:A Survey of Techniques and Results［M］//Pardalos P,Rajasekaran S,Rolim J.Handbook of Randomized Computing.Berlin,Germany:Springer,2005:255-305. ［7］Guo Bin,Yu Zhiwen,Li Dongsheng.Using the Model of Markets with Intermediaries as an Incentive Scheme for Opportunistic Social Networks［C］//Proceedings of the 10th IEEE International Conference on Ubiquitous Intelligence and Computing.Washington D.C.,USA:IEEE Press,2013:142-149. ［8］He Shibo,Shin Dong-hoon,Zhang Junshan,et al.Toward Optimal Allocation of Location Dependent Tasks in Crowdsensing［C］//Proceedings of IEEE Conference on Computer Communications.Washington D.C.,USA:IEEE Press,2014:745-753. ［9］Drosatos G,Efraimidis P S,Athanasiadis I N,et al.Privacy-preserving Computation of Participatory Noise Mapsin the Cloud［J］.Journal of Systems and Software,2014,92:170-183. ［10］Goel G,Nikzad A,Singla A.Allocating Tasks to Workers with Matching Constraints:Truthful Mechanisms for Crowdsourcing Markets［C］//Pro-ceedings of the 23rd International Conference on World Wide Web.New York,USA:ACM Press,2014:279 -280. ［11］Karamshuk D,Boldrini C,Conti M,et al.Human Mobility Models for Opportunistic Networks［J］.IEEE Communications Magazine,2011,49(12):157-165. ［12］Fahrmair M,Sitou M,Spanfelner B.Security and Privacy Rights Management for Mobile and Ubiquitous Computing［C］//Proceedings of Workshop on UbiComp Privacy.Tokyo,Japan:［s.n.］,2010:97-108. ［13］Broder A,Mitzenmacher M.Using Multiple Hash Functions to Improve IP Lookups［C］//Proceedings of the 20th Annual Joint Conference of the IEEE Computer and Communications Societies.Washington D.C.,USA:IEEE Press,2000:1454-1463. ［14］张莹,吴和生.面向多进程负载均衡的Hash算法比较与分析［J］.计算机工程,2014,40(9):71-79. ［15］Buchbinder N,Naor J S.Fair Online Load Balanc-ing［J］.Journal of Scheduling,2013,16(1):117-127. ［16］田浪军,陈卫卫,陈卫东,等.云存储系统中动态负载均衡算法研究［J］.计算机工程,2013,39(10):19-23. ［17］Sheng Xiang,Tang Jian,Zhang Weiyi.Energy-efficient Collaborative Sensing with Mobile Phones［C］//Pro-ceedings of 2012 IEEE INFOCOM.Washington D.C.,USA:IEEE Press,2012:1916-1924. ［18］Goel G,Nikzad A,Singla A.Allocating Tasks to Workers with Matching Constraints:Truthful Mecha-nisms for Crowdsourcing Markets［C］//Proceedings of the 23rd International Conference on World Wide Web Companion.New York,USA:ACM Press,2014:279-280. 编辑顾逸斐

[1]	YANG Guisong, WU Xiaotian, GAO Li, HE Xingyu. Task Allocation Towards Individual Task Quality Assurance in Mobile Crowd Sensing [J]. Computer Engineering, 2022, 48(9): 45-54.
[2]	LIU Jiahao, JIN Hanxin, QIANG Lei, GAO Guoju, DU Yang, HUANG He. Hybrid Two-Phase Task Allocation for Mobile Crowd Sensing [J]. Computer Engineering, 2022, 48(3): 139-145.
[3]	ZHOU Qiang, LI Peng, NIE Lei. User Incentive Mechanism Based on Spatial-Temporal Correlation for Crowd Sensing [J]. Computer Engineering, 2021, 47(3): 227-236.
[4]	LONG Hao, ZHANG Shukui, ZHANG Li. Privacy Protection Method Based on Voronoi Cell in Crowd Sensing [J]. Computer Engineering, 2020, 46(5): 181-186,192.
[5]	ZHANG Jide,YUAN Yin,LIU Yazhi,ZHANG Xinying,YANG Zongshuai. A Quality Information Oriented Collaboration Method for Mobile Crowd Sensing [J]. Computer Engineering, 2017, 43(7): 15-21.
[6]	SHI Tao-tao, MA Yong-zheng. Data Synchronization Strategy Based on Conflict Resolution for Research Online Mobile [J]. Computer Engineering, 2014, 40(2): 119-122,133.
[7]	HU Ai-Jun, ZHANG Yue. Data Management Approach for Large-scale Mobile Terminal [J]. Computer Engineering, 2012, 38(5): 59-61,66.
[8]	DENG Hai-Sheng, LI Jun-Fu, ZHANG Jing, NI Jing-Qing. Mobile Computing Model Based on Reflective Middleware [J]. Computer Engineering, 2012, 38(20): 278-281.
[9]	TIE Jun, ZHANG Bao-Zhe, WANG Xiao-Rong. Application of Optimistic Concurrency Protocol in Mobile Computing Environment [J]. Computer Engineering, 2011, 37(20): 264-267.
[10]	TUN Jian, YANG Run-Biao, DIAO Gui-Wen, TUN Rong-Hai, DONG Mo-Gui. Broadcast Schedule Algorithm for Request Multiply Data Items in Mobile Environment [J]. Computer Engineering, 2011, 37(2): 102-104.
[11]	WANG Feng-Liang, LV Wei-Feng, CHU Tong-Yu, LIANG Cheng-Meng. Multi-channel Data Broadcast Schedule Algorithm Based on Greedy Strategy [J]. Computer Engineering, 2011, 37(12): 179-181.
[12]	TANG Li; LEI Xiang-dong; DUAN Hong-liang. Adaptive Hybrid Broadcast in Mobile Computing Environment [J]. Computer Engineering, 2009, 35(24): 143-145.
[13]	YANG Jin-cai; GONG Song; XU Pei-hua; HU Jin-zhu. Adaptive XML Broadcast Index in Mobile Environment [J]. Computer Engineering, 2009, 35(13): 46-48,7.
[14]	LIU Bai-qiang; YE Fei-yue; JIN Tao; CHEN Shao-bin. Remote Database Access Model Based on Mobile Agent [J]. Computer Engineering, 2008, 34(16): 82-84.
[15]	ZHANG Na; ZHENG Jun. Dynamic Location Management Algorithm Based on Triangle Grid Quorum [J]. Computer Engineering, 2007, 33(22): 145-147.

Please choose a citation manager

Content to export