Deploying Hierarchical Mesh Networks for Supporting Distributed Computing in Industrial Internet of Things

被引:3
作者
Ma, Chaofan [1 ]
Zheng, Meng [2 ]
Liang, Wei [2 ]
Kasparick, Martin [3 ,4 ]
Lin, Yufeng [5 ]
机构
[1] Zhongyuan Univ Technol, Software Coll, Zhengzhou 450007, Peoples R China
[2] Chinese Acad Sci, State Key Lab Robot, Shenyang 110016, Peoples R China
[3] Tech Univ Berlin, D-10587 Berlin, Germany
[4] Fraunhofer Heinrich Hertz Inst, D-10587 Berlin, Germany
[5] Cent Queensland Univ, Ctr Intelligent Syst, Townsville, Qld 4810, Australia
来源
IEEE SYSTEMS JOURNAL | 2022年 / 16卷 / 03期
基金
中国国家自然科学基金;
关键词
Computational modeling; Industrial Internet of Things; Delays; Task analysis; Data models; Edge computing; Computer architecture; In-network computation; industrial Internet of Things (IIOT); relay node placement; wireless sensor networks; RELAY NODE PLACEMENT; WIRELESS SENSOR NETWORKS; PERFORMANCE; PARADIGM; DELAY; IOT; COMPUTATION; LATENCY; DESIGN;
D O I
10.1109/JSYST.2022.3153339
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The centralized computing model in industrial Internet of Things (IIoT) leads to large delay and unbalanced traffic, which strictly restricts the adoption of IIoT in industrial applications demanding high network performance. To cope with the problem, researchers resort to the in-network computation model in which the computation capability is distributed among nodes in IIoT. Existing works on the in-network computation assume that the network connectivity built in advance meets the performance requirement of the in-network computation model. Nevertheless, no node placement methods have been proposed to build network connectivity supporting in-network computation. For this reason, we propose an in-network-computation-oriented node placement (INP) algorithm. The INP algorithm first decomposes the whole problem into several delay constrained relay node placement problems, and then, solves them sequentially. Moreover, we prove that the INP algorithm ensures explicit time complexity and approximation ratio. Finally, we verify the efficiency of this work through extensive simulations and preliminary experiments.
引用
收藏
页码:4433 / 4444
页数:12
相关论文
共 50 条
[21]   FUSION-Fog Computing and Blockchain for Trusted Industrial Internet of Things [J].
Ceccarelli, Andrea ;
Cinque, Marcello ;
Esposito, Christian ;
Foschini, Luca ;
Giannelli, Carlo ;
Lollini, Paolo .
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT, 2022, 69 (06) :2944-2958
[22]   Coding for Distributed Fog Computing in Internet of Mobile Things [J].
Yue, Jing ;
Xiao, Ming .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2021, 20 (04) :1337-1350
[23]   A Survey on the Applications of Cloud Computing in the Industrial Internet of Things [J].
Dritsas, Elias ;
Trigka, Maria .
BIG DATA AND COGNITIVE COMPUTING, 2025, 9 (02)
[24]   Multi-CAP Assisted Intelligent Mobile Edge Computing Networks for Internet of Things [J].
Chen, Liming ;
Kuang, Xiaoyun ;
Deng, Dan ;
Zhu, Fusheng ;
Xia, Junjuan ;
Fan, Liseng .
IEEE ACCESS, 2020, 8 :137235-137243
[25]   Mobility-aware hierarchical fog computing framework for Industrial Internet of Things (IIoT) [J].
Qayyum, Tariq ;
Trabelsi, Zouheir ;
Malik, Asad Waqar ;
Hayawi, Kadhim .
JOURNAL OF CLOUD COMPUTING-ADVANCES SYSTEMS AND APPLICATIONS, 2022, 11 (01)
[26]   Mobility-aware hierarchical fog computing framework for Industrial Internet of Things (IIoT) [J].
Tariq Qayyum ;
Zouheir Trabelsi ;
Asad Waqar Malik ;
Kadhim Hayawi .
Journal of Cloud Computing, 11
[27]   Distributed Offloading in Overlapping Areas of Mobile-Edge Computing for Internet of Things [J].
Huang, Jiwei ;
Wang, Ming ;
Wu, Yuan ;
Chen, Ying ;
Shen, Xuemin .
IEEE INTERNET OF THINGS JOURNAL, 2022, 9 (15) :13837-13847
[28]   Joint Deep Reinforcement Learning and Stackelberg Game With Intervention for Heterogeneous Edge Computing in Industrial Internet of Things [J].
Cheng, Weijun ;
Wei, Wenjing ;
Liu, Xiaoshi ;
Huan, Xintao .
IEEE INTERNET OF THINGS JOURNAL, 2025, 12 (13) :25457-25471
[29]   Cooperative and Distributed Computation Offloading for Blockchain-Empowered Industrial Internet of Things [J].
Chen, Wuhui ;
Zhang, Zhen ;
Hong, Zicong ;
Chen, Chuan ;
Wu, Jiajing ;
Maharjan, Sabita ;
Zheng, Zibin ;
Zhang, Yan .
IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (05) :8433-8446
[30]   Hierarchical Edge Computing: A Novel Multi-Source Multi-Dimensional Data Anomaly Detection Scheme for Industrial Internet of Things [J].
Peng, Yuhuai ;
Tan, Aiping ;
Wu, Jingjing ;
Bi, Yuanguo .
IEEE ACCESS, 2019, 7 :111257-111270