Efficiency Optimization for Computer Network Integrated Database Empowered by Artificial Intelligence of Things Technology

Zhu Maosheng; Wang Baohan; Kang Mancong; Yu Wei; Yang Lichao

doi:10.7544/issn1000-1239.202440416

Journal of Computer Research and Development > 2024 > 61(11): 2835-2845. > DOI: 10.7544/issn1000-1239.202440416 CSTR: 32373.14.issn1000-1239.202440416

Zhu Maosheng, Wang Baohan, Kang Mancong, Yu Wei, Yang Lichao. Efficiency Optimization for Computer Network Integrated Database Empowered by Artificial Intelligence of Things Technology[J]. Journal of Computer Research and Development, 2024, 61(11): 2835-2845. DOI: 10.7544/issn1000-1239.202440416

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Efficiency Optimization for Computer Network Integrated Database Empowered by Artificial Intelligence of Things Technology

1.
China Mobile (Suzhou) Software Technology Co., Ltd., Suzhou, Jiangsu 215009
2.
China Mobile Communications Research Institute, Beijing 100053
3.
School of Public Health, Suzhou Medical College of Soochow University, Suzhou, Jiangsu 215000

Funds: This work was supported by the National Natural Science Foundation of China Enterprise Innovation and Development Joint Fund Project (U22B2020).

More Information

Author Bio:
Zhu Maosheng: born in 1998. Master. His main research interests include computing force network, database technology, and edge computing

Wang Baohan: born in 1986. Senior system architecture expert, vice general manager of Ecloud’s Database Product Department (hosted), expert of Artificial Intelligence Department of China Mobile Technology Association. His main research interests include computing force network, database theory, data mining, and intelligent data processing

Kang Mancong: born in 1995. PhD. Her main research interests include digital twin networks, machine learning, and haptic-visual communication

Yu Wei: born in 1978. Advanced system architecture expert, director of Ecloud’s Database Technology Committee. His main research interests include database kernel architecture, storage engine, and database security

Yang Lichao: born in 1992. PhD, assistant professor. Her main research interests focus on machine learning, intelligent public health management, and medical databases technology
Received Date: May 30, 2024
Revised Date: July 30, 2024
Available Online: August 13, 2024

Graphical Abstract

Abstract

Abstract

The collection, storage and sharing technology of massive perceptual data has promoted the rise of the Internet of things. Its large-scale application has put forward an urgent requirement for database to have strong data consistency and high resource efficiency. However, the existing database system architecture and management and control methods mostly reduce communication costs by reducing the amount of data transmitted and increasing node storage replicas, and lack of integrated awareness and optimization of system network resources, resulting in low database efficiency. For this reason, we construct an integrated computing network database system to drive the integrated perception representation of computing resources and networks, and enables the database with intelligent Internet of things technology (AIoT) to realize the joint intelligent scheduling of computing resources and networks, so as to reduce the overall cost and improve the efficiency of computing networks. First, we construct a distributed database network integrated with computing and network, and analyze its architecture characteristics. Then, in order to realize the unified representation of computing and communication optimization variables, an integrated cost perception model is constructed. On this basis, an intelligent one-stop resource optimization algorithm is proposed to maximize the overall computing efficiency of the database system. Finally, simulation experiments verify the superiority of the proposed architecture and algorithm in network performance, algorithm convergence, integration cost and resource efficiency.
- AIoT,
- computer network integration,
- distributed database,
- unified perception,
- efficiency optimization

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References (26)

References

[1]	Yin Huanpu, Yu Shuhui, Zhang Yingshuo, et al. Let IoT know you better: User identification and emotion recognition through millimeter-wave sensing[J]. IEEE Internet of Things Journal, 2022, 10(2): 1149−1161
[2]	Xiao Han, Zhuang Yirong, Xu Changqiao, et al. Transcoding-enabled cloud-edge-terminal collaborative video caching in heterogeneous IoT networks: An online learning approach with time-varying information[J]. IEEE Internet of Things Journal, 2024, 11(1): 296−310 doi: 10.1109/JIOT.2023.3312916
[3]	Zhang Tao, Xu Changqiao, Lian Yibo, et al. When moving target defense meets attack prediction in digital twins: A convolutional and hierarchical reinforcement learning approach[J]. IEEE Journal on Selected Areas in Communications, 2023, 41(10): 3293−3305 doi: 10.1109/JSAC.2023.3310072
[4]	Xiao Han, Xu Changqiao, Ma Yunxiao, et al. Edge intelligence: A computational task offloading scheme for dependent IoT application[J]. IEEE Transactions on Wireless Communications, 2022, 21(9): 7222−7237 doi: 10.1109/TWC.2022.3156905
[5]	刘帅,乔颖,罗雄飞,等. 时序数据库关键技术综述[J]. 计算机研究与发展,2024,61(3):614−638 doi: 10.7544/issn1000-1239.202330536 Liu Shuai, Qiao Ying, Luo Xiongfei, et al. Key techniques of time series databases: A survey[J]. Journal of Computer Research and Development, 2024, 61(3): 614−638 (in Chinese) doi: 10.7544/issn1000-1239.202330536
[6]	Rosenkrantz D J, Stearns R E, Lewis P M. System level concurrency control for distributed database systems[J]. ACM Transactions on Database System, 1978, 3((2): ): 178−198 doi: 10.1145/320251.320260
[7]	Gardarin G, Goodman N, Lindsay B G, et al. Distributed database systems[C]//Proc of the 6th Int Conf on Very Large Data Bases (VLDB ’80). New York: ACM, 1980: 201–202
[8]	Cai Hui, Qian Zhenghao, Jiang Jiang. Application of association rule algorithm in distributed new SQL database design[C]//Proc of the 2023 IEEE Int Conf on Integrated Circuits and Communication Systems (ICICACS). Piscataway, NJ: IEEE, 2023: 1−5
[9]	Mansouri Y, Prokhorenko V, Ullah F, et al. Resource utilization of distributed databases in edge–cloud environment[J]. IEEE Internet of Things Journal, 2023, 10(11): 9423−9437 doi: 10.1109/JIOT.2023.3235360
[10]	Prasetio N, Ferdinand D, Wijaya B C, et al. Performance analysis of distributed database system in cloud computing environment[C]//Proc of 9th Int Conf on Computing, Engineering and Design (ICCED). Piscataway, NJ: IEEE, 2023: 1−6
[11]	苏彦志,陈广,蒋越维. 分布式数据库发展综述[J]. 数字通信世界,2023(10):172−174 doi: 10.3969/J.ISSN.1672-7274.2023.10.056 Su Yanzhi, Chen Guang, Jiang Yuewei. Overview of development of distributed database[J]. Digital Communication World, 2023(10): 172−174 (in Chinese) doi: 10.3969/J.ISSN.1672-7274.2023.10.056
[12]	Peterson R J, Strickland J. P. Log write-ahead protocols and IMS/VS logging[C]//Proc of the 2nd ACM SIGACT-SIGMOD Symp on Principles of Database Systems(PODS ’83). New York: ACM, 1983: 216–243l
[13]	Jhingran A, Khedkar P. Analysis of recovery in a database system using a write-ahead log protocol[C]//Proc of the 1992 ACM SIGMOD Int Conf on Management of Data (SIGMOD’92). New York: ACM, 1992: 175–184
[14]	Sidell J. The Mariposa distributed database management system[C]//Proc of the 1996 ACM SIGMOD Int Conf on Management of Data (SIGMOD’96). New York: ACM, 1996: 76–80
[15]	王儒升. 分布式数据库在信息化管理系统中的应用探析[J]. 电脑知识与技术,2023,19(35):83−85 Wang Rusheng. Analysis of the application of distributed database in information management system[J]. Computer Knowledge and Technology, 2023, 19(35): 83−85 (in Chinese)
[16]	申红雪,郭延哺. 分布式数据库研究新趋势[J]. 软件,2021,42(10):31−34 doi: 10.3969/j.issn.1003-6970.2021.10.010 Shen Hongxue, Guo Yanpu. New trends in distributed database research[J]. Software, 2021, 42(10): 31−34 (in Chinese) doi: 10.3969/j.issn.1003-6970.2021.10.010
[17]	Zguem S, Chen Qichen, Yeom H Y. NF-Log: Revisiting log writes in relational database for efficient persistent memory utilization[C]//Proc of the 38th ACM/SIGAPP Symp on Applied Computing (SAC’23). New York: ACM, 2023: 305–312
[18]	Zheng Bolong, Gao Yongyong, Wan Jingyi, et al. DecLog: Decentralized logging in non-volatile memory for time series database systems[J]. Proceedings of the VLDB Endowment, 2024, 17(1): 1−14
[19]	Wang Jinjin, Du Yizhou, Wang Xiangyu, et al. TEE-assisted time-scale database management system on IoT devices[C]//Proc of the 13th Int Conf on Internet of Things( IoT ’23). New York: ACM, 2023: 253–259
[20]	Gong Xiaomin, Bai Chenchen, Ren Shuangyin, et al. A survey of compute first networking[C]//Proc of the 23rd Int Conf on Communication Technology (ICCT). Piscataway, NJ: IEEE, 2023: 688−695
[21]	中国移动通信集团有限公司. 算力网络白皮书[R]. 北京:中国移动通信集团有限公司,2021 China Mobile Communications Group Co., Ltd. Computing Power Network White Paper [R]. Beijing: China Mobile Communications Group Co., Ltd., 2021
[22]	郭凤仙,孙耀华,彭木根. 6G算力网络:体系架构与关键技术[J]. 无线电通信技术,2023,49(1):21−30 doi: 10.3969/j.issn.1003-3114.2023.01.003 Guo Fengxian, Sun Yaohua, Peng Mugen. Computing force networks in 6G: Architecture and key technologies[J]. Radio Communications Technology, 2023, 49(1): 21−30 (in Chinese) doi: 10.3969/j.issn.1003-3114.2023.01.003
[23]	阳振坤,杨传辉,韩富晟,等. OceanBase分布式关系数据库架构与技术[J]. 计算机研究与发展,2024,61(3):540−554 Yang Zhenkun, Yang Chuanhui, Han Fusheng, et al. Architecture and technology of OceanBase distributed relational database[J]. Journal of Computer Research and Development, 2024, 61(3): 540−554 (in Chinese)
[24]	Vilaplana J, Solsona F, Teixido I, et al. A queuing theory model for cloud computing[J]. The Journal of Supercomputing, 2014, 69(1): 492−507 doi: 10.1007/s11227-014-1177-y
[25]	Zhu Maosheng, Li Xi, Ji Hong, et al. Cost-aware resource allocation with probabilistic latency guarantee in B5G industrial private networks[C]//Proc of the 2022 IEEE Int Conf on Communications Workshops (ICC Workshops). Piscataway, NJ: IEEE, 2022: 532−537
[26]	Deb K, Jain H. An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, Part I: Solving problems with box constraints[J]. IEEE Transactions on Evolutionary Computation, 2014, 18(4): 577−601 doi: 10.1109/TEVC.2013.2281535

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