

浏览全部资源
扫码关注微信
1.北京市大数据中心,北京 100101
2.中国科学院自动化研究所多模态人工智能系统全国重点实验室,北京 100190
3.中国科学院自动化研究所复杂重点系统管理与控制国家实验室,北京 100190
4.澳门科技大学创新工程学院,澳门 999078
5.数据堂(北京)科技股份有限公司,北京 100192
Received:02 March 2024,
Revised:2024-05-24,
Published:15 June 2024
移动端阅览
贾晓丰,秦蕊,王寿文等.联邦服务:基于分布式数据共治的智能服务范式[J].智能科学与技术学报,2024,06(02):210-219.
JIA Xiaofeng,QIN Rui,WANG Shouwen,et al.Federated services: smart service paradigm based on distributed data co-governance[J].Chinese Journal of Intelligent Science and Technology,2024,06(02):210-219.
贾晓丰,秦蕊,王寿文等.联邦服务:基于分布式数据共治的智能服务范式[J].智能科学与技术学报,2024,06(02):210-219. DOI: 10.11959/j.issn.2096-6652.202416.
JIA Xiaofeng,QIN Rui,WANG Shouwen,et al.Federated services: smart service paradigm based on distributed data co-governance[J].Chinese Journal of Intelligent Science and Technology,2024,06(02):210-219. DOI: 10.11959/j.issn.2096-6652.202416.
随着数字化转型的加速,数据已成为驱动科技创新与经济增长的核心要素。然而,广泛存在的数据孤岛现象严重阻碍了跨领域、跨组织间的数据流通与合作,使得数据供应难以满足多样化的用户需求,数据的供需匹配面临严峻挑战。作为联邦生态的核心环节和对外赋能的重要窗口,联邦服务基于分布式数据共治原则,促进了跨领域、跨组织的数据流通与协同,为智能的供需匹配提供了一种有效的技术框架。首先,探讨联邦服务在联邦生态中的重要地位以及与联邦生态各环节的关系。其次,提出联邦服务的5层基本框架,并探讨其核心优势。在此基础上,提出联邦服务的关键支撑技术,主要包括区块链和去中心化自治组织与运营、大语言模型和场景工程、分布式计算和边缘计算、加密技术和隐私计算。最后,以数据与场景的供需匹配为应用案例,介绍联邦服务如何实现智能的供需匹配。提出的联邦服务理论与技术对于构建基于分布式数据共治的智能服务范式具有重要意义。
The acceleration of digital transformation has made data a core element driving technological innovation and economic growth. However
the widespread phenomenon of data island severely hinders data circulation and collaboration across different fields and organizations
making it difficult for data supply to meet the diverse needs of users
thus creating a dilemma in matching data supply and demand. Serving as the core link in the federated ecology and an important window for external empowerment
federated services provide an innovative solution for data circulation and utilization under the principle of distributed data co-governance
thereby enabling the intelligent matching of supply and demand. Firstly
this paper delves into the pivotal role of federated services within the federated ecology
and examines the relationship between federated services and federated ecology's key components. Secondly
it presents a five-layer basic framework of federated services and discusses its core advantages. On this basis
the paper proposes the key supporting technologies for federated services
including blockchain and decentralized autonomous organizations and operations
large language models and scenario engineering
distributed computing and edge computing
as well as encryption technology and privacy computing. Finally
taking the supply-demand matching problem of data and scenarios as a case study
the paper illustrates how federated services achieve intelligent matching of demand and supply. The federated services proposed in this paper holds significant implications for constructing a smart service paradigm based on distributed data co-governance.
刘昕, 王晓, 张卫山, 等. 平行数据: 从大数据到数据智能[J]. 模式识别与人工智能, 2017, 30(8): 673-681.
LIU X, WANG X, ZHANG W S, et al. Parallel data: from big data to data intelligence[J]. Pattern Recognition and Artificial Intelligence, 2017, 30(8): 673-681.
贾晓丰, 高嵩, 周琰, 等. 一种面向超大城市治理的数据高效跨域流通技术框架[J]. 数据与计算发展前沿, 2023, 5(5): 35-45.
JIA X F, GAO S, ZHOU Y, et al. A technical framework of efficient cross-domain data circulation for mega-city governance[J]. Frontiers of Data & Computing, 2023, 5(5): 35-45.
贾晓丰, 梁郑丽, 任锦鸾. 多源信息协同[M]. 北京: 清华大学出版社, 2016.
JIA X F, LIANG Z L, REN J L. Multi-source information collaboration[M]. Beijing: Tsinghua University Press, 2016.
TU J, FAN J, TANG N, et al. Unicorn: a unified multi-tasking model for supporting matching tasks in data integration[C]//Proceedings of the ACM on Management of Data. New York: ACM, 2023: 1-26.
王飞跃, 王艳芬, 陈薏竹, 等. 联邦生态:从联邦数据到联邦智能[J]. 智能科学与技术学报, 2020, 2(4): 305-311.
WANG F Y, WANG Y F, CHEN Y Z, et al. Federated ecology: from federated data to federated intelligence[J]. Chinese Journal of Intelligent Science and Technology, 2020, 2(4): 305-311.
LI J J, QIN R, GUAN S T, et al. Blockchain intelligence: intelligent blockchains for web 3.0 and beyond[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024: 1-10.
QIN R, YUAN Y, WANG F Y. Blockchain-based knowledge automation for CPSS-oriented parallel management[J]. IEEE Transactions on Computational Social Systems, 2020, 7(5): 1180-1188.
李娟娟, 秦蕊, 丁文文, 等. 基于Web3的去中心化自治组织与运营新框架[J]. 自动化学报, 2023, 49(5): 985-998.
LI J J, QIN R, DING W W, et al. A new framework for Web3-powered decentralized autonomous organizations and operations[J]. Acta Automatica Sinica, 2023, 49(5): 985-998.
WANG F Y, DING W W, QIN R, et al. Parallel philosophy for MetaOrganizations with MetaOperations: from Leibniz's Monad to HanoiDAO[J]. IEEE Transactions on Computational Social Systems, 2022, 9(3): 658-666.
QIN R, DING W W, LI J J, et al. Web3-based decentralized autonomous organizations and operations: architectures, models, and mechanisms[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2023, 53(4): 2073-2082.
WANG F Y, LI J J, QIN R, et al. ChatGPT for computational social systems: from conversational applications to human-oriented operating systems[J]. IEEE Transactions on Computational Social Systems, 2023, 10(2): 414-425.
QIN R, WANG F Y, ZHENG X L, et al. Sora for computational social systems: from counterfactual experiments to artificiofactual experiments with parallel intelligence[J]. IEEE Transactions on Computational Social Systems, 2024, 11(2): 1531-1550.
石庆松, 秦蕊, 肖鹏, 等. 基于联盟链的电力物资采购数据共享激励机制[J]. 中国电力, 2022, 55(3): 87-96.
SHI Q S, QIN R, XIAO P, et al. Incentive mechanism for data sharing of power material procurement based on consortium blockchain[J]. Electric Power, 2022, 55(3): 87-96.
LI J J, LI J Q, WANG X, et al. Multi-blockchain based data trading markets with novel pricing mechanisms[J]. IEEE/CAA Journal of Automatica Sinica, 2023, 10(12): 2222-2232.
WANG F Y, QIN R, CHEN Y Z, et al. Federated ecology: steps toward confederated intelligence[J]. IEEE Transactions on Computational Social Systems, 2021, 8(2): 271-278.
WANG F Y, ZHANG W S, TIAN Y L, et al. Federated data: toward new generation of credible and trustable artificial intelligence[J]. IEEE Transactions on Computational Social Systems, 2021, 8(3): 538-545.
朱静, 王飞跃, 王戈, 等. 联邦控制: 面向信息安全和权益保护的分布式控制方法[J]. 自动化学报, 2021, 47(8): 1912-1920.
ZHU J, WANG F Y, WANG G, et al. Federated control: a distributed control approach towards information security and rights protection[J]. Acta Automatica Sinica, 2021, 47(8): 1912-1920.
WANG F Y, ZHU J, QIN R, et al. Federated control: toward information security and rights protection[J]. IEEE Transactions on Computational Social Systems, 2021, 8(4): 793-798.
WANG F Y, QIN R, LI J J, et al. Federated management: toward federated services and federated security in federated ecology[J]. IEEE Transactions on Computational Social Systems, 2021, 8(6): 1283-1290.
贾晓丰, 高嵩, 江茜, 等. 面向城市复杂系统的社会计算关键技术研究[J]. 智能科学与技术学报, 2021, 3(2): 228-233.
JIA X F, GAO S, JIANG X, et al. Research on key technologies of social computing for urban complex system[J]. Chinese Journal of Intelligent Science and Technology, 2021, 3(2): 228-233.
QIN R, LI J J, LIANG X L, et al. Management-oriented operating systems: harnessing the power of DAOs and foundation models[C]//Proceedings of the 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC). Piscataway: IEEE Press, 2023: 3180-3185.
李娟娟, 管桑田, 秦蕊, 等. 智能区块链与区块链智能:构筑DePIN的基础设施智能[J]. 智能科学与技术学报, 2024, 6(1): 5-16.
LI J J, GUAN S T, QIN R, et al. Intelligent blockchains and blockchain intelligence: the infrastructure intelligence for DePIN[J]. Chinese Journal of Intelligent Science and Technology, 2024, 6(1): 5-16.
WANG G, QIN R, LI J J, et al. A novel DAO-based parallel enterprise management framework in Web3 era[J]. IEEE Transactions on Computational Social Systems, 2024, 11(1): 839-848.
QIN R, LI J J, WANG F Y. MetaEconomics and MetaManagement for MetaCities and MetaSocieties in Metaverse[J]. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024: 1-10.
CHANG Y P, WANG X, WANG J D, et al. A survey on evaluation of large language models[J]. ACM Transactions on Intelligent Systems and Technology, 15(3): 1-45.
WANG L, MA C, FENG X Y, et al. A survey on large language model based autonomous agents[J]. Frontiers of Computer Science, 2024, 18(6): 186345.
LI X, SONG R, FAN J F, et al. Development and testing of advanced driver assistance systems through scenario-based systems engineering[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(8): 3968-3973.
CHANG C, CAO D P, CHEN L, et al. MetaScenario: a framework for driving scenario data description, storage and indexing[J]. IEEE Transactions on Intelligent Vehicles, 2023, 8(2): 1156-1175.
DE GELDER E, PAARDEKOOPER J P, SABERI A K, et al. Towards an ontology for scenario definition for the assessment of automated vehicles: an object-oriented framework[J]. IEEE Transactions on Intelligent Vehicles, 2022, 7(2): 300-314.
JIANG Y N, KANG J W, NIYATO D, et al. Reliable distributed computing for Metaverse: a hierarchical game-theoretic approach[J]. IEEE Transactions on Vehicular Technology, 2023, 72(1): 1084-1100.
施巍松, 张星洲, 王一帆, 等. 边缘计算: 现状与展望[J]. 计算机研究与发展, 2019, 56(1): 69-89.
SHI W S, ZHANG X Z, WANG Y F, et al. Edge computing: state-of-the-art and future directions[J]. Journal of Computer Research and Development, 2019, 56(1): 69-89.
GONG C, LIN F H, GONG X W, et al. Intelligent cooperative edge computing in Internet of things[J]. IEEE Internet of Things Journal, 2020, 7(10): 9372-9382.
HAMDAN S, AYYASH M, ALMAJALI S. Edge-computing architectures for Internet of things applications: a survey[J]. Sensors, 2020, 20(22): 6441.
张鹏, 李美鹏, 郭兆中, 等. 基于隐私计算技术的数据安全共享交互框架[J]. 网络安全与数据治理, 2023, 42(12): 54-59.
ZHANG P, LI M P, GUO Z Z, et al. A data security sharing and interaction framework based on privacy computing technology[J]. Cyber Security and Data Governance, 2023, 42(12): 54-59.
0
Views
303
下载量
0
CSCD
Publicity Resources
Related Articles
Related Author
Related Institution
京公网安备11010802024621