面向元宇宙的云边端协同大数据管理

doi:10.11959/j.issn.2096-0271.2023011

大数据 ›› 2023, Vol. 9 ›› Issue (1): 63-77.doi: 10.11959/j.issn.2096-0271.2023011

• 专题：元宇宙与大数据 • 上一篇下一篇

面向元宇宙的云边端协同大数据管理

朱锐, 王宏志, 崔双双, 张恺欣, 燕钰

哈尔滨工业大学计算机科学与技术学院，黑龙江哈尔滨 150000

出版日期:2023-01-15 发布日期:2023-01-01
作者简介:朱锐（1998- ），女，哈尔滨工业大学计算机科学与技术学院博士生，发表EI检索论文1篇，主要研究方向为AI4DB、大数据、数据库索引
王宏志（1978- ），男，哈尔滨工业大学计算学部长聘教授、博士生导师，计算机科学与工程系主任，海量数据计算研究中心主任，数据科学与大数据技术专业负责人，美国加州大学欧文分校博士后，微软亚洲研究院铸星计划访问学者，青年龙江学者。主要研究方向为大数据治理、大数据管理与分析、数据库系统、工业大数据等。在国内外重要会议和期刊发表学术论文300余篇，出版学术专著4本。论文被SCI收录百余次，他引4 000余次，授权发明专利32项。获微软学者、中国优秀数据库工程师、IBM博士英才等称号，获黑龙江省自然科学奖一等奖和教育部高等学校科技进步奖一等奖，获黑龙江省青年科技奖、宝钢优秀教师奖、CSC-IBM奖教金。主持国家自然科学基金重点项目、国家支撑计划课题、国家博士后特别资助项目等10余个项目，主讲的课程获批国家一流线上课程。中国计算机学会杰出会员，ACM SIGMOD中国秘书长、教育部高等学校计算机类专业教学指导委员会计算机系统专家委员会委员、中国计算机学会数据库专业委员会常务委员、中国计算机学会大数据专家委员会委员、哈尔滨工业大学计算学部校友会秘书长、ACM数据科学学科标准编写组专家、黑龙江省“头雁团队”成员
崔双双（1997- ），女，哈尔滨工业大学计算机科学与技术学院博士生，发表EI检索论文两篇，主要研究方向为数据库存储、AI4DB
张恺欣（1999- ），男，哈尔滨工业大学计算机科学与技术学院博士生，在TKDE期刊发表过论文1篇，公示专利两篇，主要研究方向为数据库系统、AI4DB
燕钰（1996- ），女，哈尔滨工业大学计算机科学与技术学院博士生，发表SCI检索论文1篇、EI检索论文3篇，主要研究方向为AI4DB、大数据
基金资助:
国家自然科学基金资助项目(62232005)

Cloud-edge-end collaborative big data management for metaverse

Rui ZHU, Hongzhi WANG, Shuangshuang CUI, Kaixin ZHANG, Yu YAN

Faculty of Computing, Harbin Institute of Technology, Harbin 150000, China

Online:2023-01-15 Published:2023-01-01
Supported by:
The National Natural Science Foundation of China(62232005)

摘要/Abstract

摘要：

随着元宇宙的用户不断增多，数据量也相应地增长，这给元宇宙的数据管理带来了挑战。大数据管理技术对元宇宙的实现至关重要。对元宇宙中的数据管理技术进行了讨论，将元宇宙分解为云、边、端3个层次，分析了元宇宙中的大数据的特点和数据管理特点，讨论了面向元宇宙的云边端数据管理的4个挑战，并从数据模型、数据同步、数据存取、查询优化4个方面提出相应的研究路线。

关键词: 元宇宙, 数据管理, 数据库

Abstract:

With the increasing number of users in the metaverse, the data also increases accordingly, which brings challenges to the data management of the metaverse.Big data management techniques are essential to realizing the metaverse.Therefore, data management technology in the metaverse was discussed.The metaverse was decomposed into three levels cloud, edge, and end.The massive data in the metaverse was analyzed.The four challenges of data management in the metaverse were discussed, and the corresponding research routes were put forward from four aspects of data synchronization, data access, data model, and query optimization.

Key words: metaverse, data management, database

中图分类号:

TP391.9

朱锐, 王宏志, 崔双双, 张恺欣, 燕钰. 面向元宇宙的云边端协同大数据管理[J]. 大数据, 2023, 9(1): 63-77.

Rui ZHU, Hongzhi WANG, Shuangshuang CUI, Kaixin ZHANG, Yu YAN. Cloud-edge-end collaborative big data management for metaverse[J]. Big Data Research, 2023, 9(1): 63-77.

图/表 2

参考文献 44

[1]	WIEDERHOLD B K . Ready (or not) player one:initial musings on the metaverse[J]. Cyberpsychology,Behavior and Social Networking, 2022,25(1): 1-2.
[2]	RATCLIFFE J , SOAVE F , BRYANKINNS N ,et al. Extended reality (XR) remote research:a survey of drawbacks and opportunities[C]// Proceedings of 2021 CHI Conference on Human Factors in Computing Systems. New York:ACM Press, 2021: 1-13.
[3]	XI N N , CHEN J , GAMA F ,et al. The challenges of entering the metaverse:an experiment on the effect of extended reality on workload[J]. Information Systems Frontiers:A Journal of Research and Innovation, 2022:Accepted.
[4]	HWANG G J , CHIEN S Y . Definition,roles,and potential research issues of the metaverse in education:an artificial intelligence perspective[J]. Computers and Education:Artificial Intelligence, 2022,3:100082.
[5]	MOHANTA B K , JENA D , PANDA S S ,et al. Blockchain technology:a survey on applications and security privacy Challenges[J]. Internet of Things, 2019,8:100107.
[6]	YOU X H , WANG C X , HUANG J ,et al. Towards 6G wireless communication networks:vision,enabling technologies,and new paradigm shifts[J]. Science China Information Sciences, 2020,64(1): 1-74.
[7]	TANG F X , CHEN X H , ZHAO M ,et al. The roadmap of communication and networking in 6G for the metaverse[J]. IEEE Wireless Communications, 2022(99): 1-15.
[8]	NG W C , LIM W Y B , NG J S ,et al. Optimal stochastic coded computation offloading in unmanned aerial vehicles network[C]// Proceedings of 2021 IEEE Global Communications Conference. Piscataway:IEEE Press, 2021: 1-6.
[9]	YU X D , OWENS D , KHAZANCHI D . Building socioemotional environments in metaverses for virtual teams in healthcare:a conceptual exploration[C]// Health Information Science.[S.l.:s.n.], 2012: 4-12.
[10]	JEONG H , YI Y , KIM D . An innovative e-commerce platform incorporating metaverse to live commerce[J]. International Journal of Innovative Computing,Information and Control, 2022,18(1): 221-229.
[11]	KWON C . Smart city-based metaverse a study on the solution of urban problems[J]. Journal of the Chosun Natural Science, 2021,14(1): 21-26.
[12]	OOI B C , TAN K L , TUNG A ,et al. Sense the physical,walkthrough the virtual,manage the metaverse:a datacentric perspective[J]. arXiv preprint, 2022,arXiv:2206.10326.
[13]	COUSINS K C , ROBEY D . Human agency in a wireless world:patterns of technology use in nomadic computing environments[J]. Information and Organization, 2005,15(2): 151-180.
[14]	JIN L , ROBEY D . Bridging social and technical interfaces in organizations:an interpretive analysis of timespace distanciation[J]. Information and Organization, 2008,18(3): 177-204.
[15]	PINSONNEAULT A , CAYA O . Virtual teams[J]. International Journal of e-Collaboration, 2005,1(3): 1-16.
[16]	QIAN L P , WU Y , YU N N ,et al. Learning driven NOMA assisted vehicular edge computing via underlay spectrum sharing[J]. IEEE Transactions on Vehicular Technology, 2021,70(1): 977-992.
[17]	GOUDARZI M , WU H M , PALANISWAMI M ,et al. An application placement technique for concurrent IoT applications in edge and fog computing environments[J]. IEEE Transactions on Mobile Computing, 2021,20(4): 1298-1311.
[18]	DAI M J , ZHENG Z Y , ZHANG S L ,et al. SAZD:a low computational load coded distributed computing framework for IoT systems[J]. IEEE Internet of Things Journal, 2020,7(4): 3640-3649.
[19]	THOMASON J . Metahealth-how will the metaverse change health care?[J]. Journal of Metaverse, 2021,1(1): 13-16.
[20]	KASAPAKIS V , GAVALAS D . Usergenerated content in pervasive games[J]. Computers in Entertainment, 2017,16(1): 1-23.
[21]	YANG Q L , ZHAO Y T , HUANG H W ,et al. Fusing blockchain and AI with metaverse:a survey[J]. IEEE Open Journal of the Computer Society, 2022,3: 122-136.
[22]	HUYNH-THE T , PHAM Q V , PHAM X Q ,et al. Artificial intelligence for the metaverse:a survey[J]. Engineering Applications of Artificial Intelligence, 2023,117:105581.
[23]	NING H S , WANG H , LIN Y J ,et al. A survey on metaverse:the state-ofthe-art,technologies,applications,and challenges[J]. arXiv preprint, 2021,arXiv:2111.09673.
[24]	DATE C J . A guide to the SQL standard(Second Edition)[M].[S.l.]: Addison-Wesley, 1989.
[25]	DEUTSCH A , SUI L , VIANU V . XML path language (xpath) version 1.0.w3c recommendation,the world wide web consortium[J]. Journal of Computer and System Sciences, 1999,73(3): 442-474.
[26]	REST O V , HONG S , KIM J ,et al. PGQL:a property graph query language[C]// Proceedings of the 4th International Workshop on Graph Data Management Experiences and Systems,New York:ACM Press, 2016.
[27]	BONNET P , GEHRKE J , SESHADRI P . Towards sensor database systems[C]// Proceedings of the 2nd International Conference on Mobile Data Management. New York:ACM Press, 2001: 3-14.
[28]	DIALLO O , RODRIGUES J J P C , SENE M . Real-time data management on wireless sensor networks:a survey[J]. Journal of Network and Computer Applications, 2012,35(3): 1013-1021.
[29]	KANZAKI A , HARA T , ISHI Y ,et al. X-Sensor:wireless sensor network testbed integrating multiple networks[M]// Wireless sensor network technologies for the Information explosion era. Heidelberg: Springer, 2010: 249-271.
[30]	ELIAS A G F , RODRIGUES J J P C , OLIVEIRA L M L ,et al. A ubiquitous model for wireless sensor networks monitoring[C]// Proceedings of 2012 6th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing. Piscataway:IEEE Press, 2012: 835-839.
[31]	PRASAD S , AVINASH S B . Smart meter data analytics using OpenTSDB and Hadoop[C]// Proceedings of 2013 IEEE Innovative Smart Grid Technologies-Asia. Piscataway:IEEE Press, 2013: 1-6.
[32]	QIU Y J , ZHU X H , LU J . Fitness monitoring system based on Internet of Things and big data analysis[J]. IEEE Access, 2021,9: 8054-8068.
[33]	BEERMANN T , ALEKSEEV A , BABERIS D ,et al. Implementation of ATLAS Distributed Computing monitoring dashboards using InfluxDB and Grafana[J]. EPJ Web of Conferences, 2020,245:03031.
[34]	GHEMAWAT S , GOBIOFF H , LEUNG S T . The Google file system[J]. ACM SIGOPS Operating Systems Review, 2003,37(5): 29-43.
[35]	LAKSHMAN A , MALIK P . Cassandra:a decentralized structured storage system[J]. ACM SIGOPS Operating Systems Review, 2010,44(2): 35-40.
[36]	DECANDIA G , HASTORUN D , JAMPANI M ,et al. Dynamo:amazon’s highly available key-value store[J]. ACM SIGOPS Operating Systems Review, 2007,41(6): 205-220
[37]	WU S , WU K L . An indexing framework for efficient retrieval on the cloud[J]. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering, 2009,32(1): 75-82.
[38]	WU S , JIANG D W , OOI B C ,et al. Efficient B-tree based indexing for cloud data processing[J]. Proceedings of the VLDB Endowment, 2010,3(1/2): 1207-1218.
[39]	WANG J B , WU S , GAO H ,et al. Indexing multi-dimensional data in a cloud system[C]// Proceedings of the ACM SIGMOD International Conference on Management of Data. New York:ACM Press, 2010: 591-602.
[40]	NGUYEN T D T , YONG C H , PHAM X Q ,et al. An index scheme for similarity search on cloud computing using MapReduce over Docker container[C]// Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication. New York:ACM Press, 2016: 1-6.
[41]	ZHANG X Y , AI J , WANG Z Y ,et al. An efficient multi-dimensional index for cloud data management[C]// Proceedings of the 1st International Workshop on Cloud Data Management. New York:ACM Press, 2009: 17-24.
[42]	CHENG C L , SUN C J , XU X L ,et al. A multi-dimensional index structure based on improved VA-file and CAN in the cloud[J]. International Journal of Automation and Computing, 2014,11(1): 109-117.
[43]	CHEN G , VO H T , WU S ,et al. A framework for supporting DBMS-like indexes in the cloud[J]. Proceedings of the VLDB Endowment, 2011,4(11): 702-713.
[44]	TAN K L . Query optimization in sensor networks[M]// Encyclopedia of database systems (2nd ed.).[S.l:s.n.], 2018.

面向元宇宙的云边端协同大数据管理

Cloud-edge-end collaborative big data management for metaverse

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