1
Department of Electrical and Electronic Engineering, Universiti Putra Malaysia, Malaysia
(mzk@upm.edu.my)
2
mhmed.algrnaodi.1@ens.etsmtl.ca
(Electrical Engineering Department, Ecole de technologie superieure, Montreal, Canada)
3
College of Computer Information Technology, American University in the Emirates, Dubai, UAE
(ahmed.almasri@aue.ae)
Abstract :
In recent years, a variety of wired and wireless network communication protocols in the field of industrial control have become increasingly mature. The purpose of this paper is to provide a Shared network communication bandwidth optimization management algorithm for large-scale industrial networked control systems in Internet of things applications. This algorithm is based on the generalized geometric convex optimization method and can realize the optimal allocation of Shared network communication bandwidth resources. L2 networked control systems is used in this paper for the establishment of various numerical relations between the control performance and the communication network parameters. Based on the generalized geometric convex optimization method for the numerical relationship between convex analysis and fitting, convexity, and with the convex analysis and the numerical relationship between convexity fitting as constraint conditions, the results of integrity for networked control systems with large-scale resource allocation target will share the optimal management of network resources as a generalized geometric convex optimization problem. Using convex optimization software package for optimizing the optimal global solution of management problem, i. e. the optimal allocation of resources, the algorithm realizes the stability of each networked control system and achieve optimal L2 control performance. It is concluded that the predetermined transmission rate between the network node one and network node two, the data flow information sent by the network node two to the network node one is read, the delay time and packet loss rate between the two nodes are determined, the delay time is reduced by about 8 seconds, and the packet loss rate is greatly reduced by 78%.
Keywords :
Shared Network; Communication Bandwidth Optimization; Internet of Things Environment; Sensor Nodes; Management Algorithm
References :
[1] Tim Roughgarden, Okke Schrijvers. Network Cost-Sharing without Anonymity[J]. Acm Transactions on Economics & Computation, 2016, 4(2):8.
[2] Kee-Young Kwahk, Do-Hyung Park. The effects of network sharing on knowledge-sharing activities and job performance in enterprise social media environments[J]. Computers in Human Behavior, 2016, 55(9):826-839.
[3] Wei LIU, Rui HU, Ryoichi SHINKUMA. A Fair Resource Sharing Mechanism between Mobile Virtual Network Operators[J]. Ieice Trans Commun, 2015, E98.B(11):2141-2150.
[4] Martin I Montenovo, Ryan N Hansen, André A S Dick. Donor Age Still Matters in Liver Transplant: Results From the United Network for Organ Sharing-Scientific Registry of Transplant Recipients Database[J]. Experimental & Clinical Transplantation Official Journal of the Middle East Society for Organ Transplantation, 2016, 15(5):657-698.
[5] Lincoln Nadauld, Derrick Haslem, Paul D. Tittel. Abstract 998: OPeN: the oncology precision network data sharing consortium[J]. Cancer Research, 2017, 77(13 Supplement):998-998.
[6] D.J. Usatin, E. R. Perito, A. M. Posselt. Under Utilization of Pancreas Transplants in Cystic Fibrosis Recipients in the United Network Organ Sharing (UNOS) Data 1987-2014[J]. American Journal of Transplantation, 2015, 16(5):n/a-n/a.
[7] soha Farhat, Abed Ellatif Samhat, Samer Lahoud. Radio Access Network Sharing in 5G: Strategies and Benefits[J]. Wireless Personal Communications, 2017, 96(1):1 – 26.
[8] Konstantinos Samdanis, Xavier Costa-Perez, Vincenzo Sciancalepore. From Network Sharing to Multi-tenancy: The 5G Network Slice Broker[J]. IEEE Communications Magazine, 2016, 54(7):68.
[9] Liyan Sun, Zhiwen Fan, Yue Huang. A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction[J]. IEEE Transactions on Image Processing, 2018, PP(99):92.
[10] Huaqing Li, Guo Chen, Tingwen Huang. High-Performance Consensus Control in Networked Systems With Limited Bandwidth Communication and Time-Varying Directed Topologies[J]. IEEE Transactions on Neural Networks & Learning Systems, 2016, 28(5):1-12.
[11] Jeffrey M. Walls, Alexander G. Cunningham, Ryan M. Eustice. Cooperative localization by factor composition over a faulty low-bandwidth communication channel[J]. Proceedings - IEEE International Conference on Robotics and Automation, 2015, 2015(8):401-408.
[12] G.-R. Zhao, X. Han, J.-H. Lu. A decentralized fusion estimator using data-driven communication strategy subject to bandwidth constraints[J]. Acta Automatica Sinica, 2015, 41(9):1649-1658.
[13] MOUSUMI PAUL, Gautam Sanyal, Debabrata Samanta. Admission Control Algorithm Based-on Effective Bandwidth in V2I Communication[J]. Iet Communications, 2018, 12(6):78.
[14] Jagpal S Klair, Mohit Girotra, Laura F Hutchins. Ipilimumab-Induced Gastrointestinal Toxicities: A Management Algorithm[J]. Digestive Diseases & Sciences, 2016, 61(7):2132-2139.
[15] Nan Chi Nan Chi, Jiaqi Zhao Jiaqi Zhao, Zhixin Wang Zhixin Wang. Bandwidth-efficient visible light communication system based on faster-than-Nyquist pre-coded CAP modulation[J]. Chinese Optics Letters, 2017, 15(8):080601.
[16] Jin-Wei Shi, Kai-Lun Chi, Jhih-Min Wun. III-Nitride Based Cyan Light-Emitting Diodes with GHz Bandwidth for High-Speed Visible Light Communication[J]. IEEE Electron Device Letters, 2016, 37(7):1-1.
[17] Hamidreza Jafarian. Hybrid Current-/Voltage-Mode Control Scheme for Distributed AC-Stacked PV Inverter With Low-Bandwidth Communication Requirements[J]. IEEE Transactions on Industrial Electronics, 2017, 65(1):254-268.
[18] Pei-Yun Tsai, Po-Cheng Lo, Fong-Jay Shih. A 4 $\\times$ 4 MIMO-OFDM Baseband Receiver With 160 MHz Bandwidth for Indoor Gigabit Wireless Communications[J]. Circuits & Systems I Regular Papers IEEE Transactions on, 2015, 62(12):1-11.
[19] Hossein Roufarshbaf, Upamanyu Madhow, Mark Rodwell. Analog Multiband: Efficient Bandwidth Scaling for mm-Wave Communication[J]. IEEE Journal of Selected Topics in Signal Processing, 2016, 10(3):1-1.
[20] Huamao Huang, Xin Xie, Rulian Wen. Optimized photoelectric receiver to enhance modulation bandwidth of visible light communication system[J]. Optical & Quantum Electronics, 2018, 50(1):43.
[21] Sean Barker, David Irwin, Prashant Shenoy. Pervasive Energy Monitoring and Control Through Low-Bandwidth Power Line Communication[J]. IEEE Internet of Things Journal, 2017, 4(5):1349-1359.
[22] Xiaoyan Liu, Pengfei Tian, Zixian Wei. Gbps long-distance real-time visible light communications using a high-bandwidth GaN- based micro-LED[J]. IEEE Photonics Journal, 2017, PP(99):1-1.
[23] Liudong Zuo, Michelle M. Zhu, Chase Q. Wu. Concurrent bandwidth scheduling for big data transfer over a dedicated channel[J]. International Journal of Communication Networks & Distributed Systems, 2015, 15(2/3):169.
[24] Filipe Betzel, Karen Khatamifard, Harini Suresh. Approximate Communication: Techniques for Reducing Communication Bottlenecks in Large-Scale Parallel Systems[J]. Acm Computing Surveys, 2018, 51(1):1-32.
[25] Nasser Torabi, Behrouz Shahgholi Ghahfarokhi. A bandwidth-efficient and fair CSMA/TDMA based multichannel MAC scheme for V2V communications[J]. Telecommunication Systems, 2016, 64(2):1-24.
| Style | # |
|---|---|
| MLA | M. Z. A. Ab Kadir, Mhmed Algrnaodi , Ahmed N. Al-Masri. "Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications." International Journal of Wireless and Ad Hoc Communication, Vol. 2, No. 1, 2021 ,PP. 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |
| APA | M. Z. A. Ab Kadir, Mhmed Algrnaodi , Ahmed N. Al-Masri. (2021). Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications. Journal of International Journal of Wireless and Ad Hoc Communication, 2 ( 1 ), 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |
| Chicago | M. Z. A. Ab Kadir, Mhmed Algrnaodi , Ahmed N. Al-Masri. "Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications." Journal of International Journal of Wireless and Ad Hoc Communication, 2 no. 1 (2021): 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |
| Harvard | M. Z. A. Ab Kadir, Mhmed Algrnaodi , Ahmed N. Al-Masri. (2021). Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications. Journal of International Journal of Wireless and Ad Hoc Communication, 2 ( 1 ), 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |
| Vancouver | M. Z. A. Ab Kadir, Mhmed Algrnaodi , Ahmed N. Al-Masri. Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications. Journal of International Journal of Wireless and Ad Hoc Communication, (2021); 2 ( 1 ): 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |
| IEEE | M. Z. A. Ab Kadir, Mhmed Algrnaodi, Ahmed N. Al-Masri, Optimal Algorithm for Shared Network Communication Bandwidth in IoT Applications, Journal of International Journal of Wireless and Ad Hoc Communication, Vol. 2 , No. 1 , (2021) : 33-48 (Doi : https://doi.org/10.54216/IJWAC.020103) |