Optimal Data Transmission in Internet of Things based on Wireless Sensor Networks by Combining Linear Programming and Minimum Spanning Tree
Subject Areas : electrical and computer engineeringM. Heydarian 1 * , Sagar Gorbani 2
1 - Dept. of Info. Tech. and Comp. Eng., Azarbijan Shahid Madani Universityو ،شذقهظو ]قشد
2 - Dept. of Info. Tech. and Comp. Eng., Azarbijan Shahid Madani Universityو ،شذقهظو ]قشد
Keywords: Optimal transmission, minimum spanning tree, wireless sensor network, network lifetime.,
Abstract :
In Mobile Internet of Things (MIoT) or Wireless Sensor Network (WSN) networks, which can be fog-based, there are challenges such as energy consumption management, Quality of Service (QoS) improvement, and reliability, which have attracted a lot of research. have given. Limited resources and dynamic topology in these networks have made these challenges more complicated. In the Internet of Things network, wireless sensors use a battery with a limited capacity to supply their energy, so operations such as data collection and routing that cause energy consumption need to be optimized. In order to manage these challenges, the principles of green network design and optimization methods can be used to help increase the life of the network, optimize energy consumption, and increase network efficiency. In this article, linear optimization methods and graph theory-based algorithms are used, and a new routing algorithm is presented that can improve optimal energy consumption, QoS, network lifetime, and efficiency. Mathematical modeling and simulation of the new method show that this algorithm, compared to existing methods, can pass more data through the network by taking shorter routes and use the network resources optimally
[1] M. Tanveer, and A. Badshah, "CMAF-IIoT: Chaotic map-based authentication framework for industrial Internet of things," Internet of Things, vol. 23, Article ID: 100902, Oct. 2023.
[2] Q. Qi, Z. Xu, and P. Rani, "Big data analytics challenges to implementing the intelligent industrial Internet of things (IIoT) systems in sustainable manufacturing operations," Technological Forecasting and Social Change, vol. 190, Article ID: 122401, May 2023.
[3] V. R. Kebande, "Industrial internet of things (IIoT) forensics: The forgotten concept in the race towards industry 4.0," Forensic Science International, vol. 5, Article ID: 100257, Jul. 2022.
[4] H. K. Apat and R. N. Sahoo, "A comprehensive review on Internet of Things application placement in Fog computing environment," Internet of Things, vol. 23, Article ID: 100866, Oct. 2023.
[5] F. Safara, A. Souri, T. Baker, I. A. Ridhawi, and M. Aloqaily, "PriNergy: A priority-based energy-efficient routing method for IoT systems," The Journal of Supercomputing, vol. 76, no. 11, pp. 8609-8626, Nov. 2020.
[6] J. Lin, W. Yu, N. Zhang, X. Yang, H. Zhang, and W. Zhao, "A survey on internet of things: Architecture, enabling technologies, security and privacy, and applications," IEEE Internet of Things Journal, vol. 4, no. 5, pp. 1125-1142, Mar. 2017.
[7] T. D. Nguyen, J. Y. Khan, and D. T. Ngo, "An effective energy-harvesting-aware routing algorithm for WSN-based IoT applications," in Proc. IEEE Int. Conf. on Communications, 6 pp., Paris, France, 21-25 May 2017.
[8] P. Maheshwari, A. K. Sharma, and K. Verma, "’Energy efficient cluster based routing protocol for WSN using butterfly optimization algorithm and ant colony optimization," Ad Hoc Networks, vol. 110, Article ID: 102317, 2021.
[9] P. G. V. Naranjo, Z. Pooranian, M. Shojafar, M. Conti, and R. Buyya, "FOCAN: A fog-supported smart city network architecture for management of applications in the Internet of everything environments," Journal of Parallel and Distributed Computing, vol. 132, pp. 274-283, Oct. 2019.
[10] W. B. Heinzelman, Application-Specific Protocol Architectures for Wireless Networks, PhD. Thesis, Massachusetts Institute of Technology, 2000.
[11] W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, "Energy-efficient communication protocol for wireless microsensor networks," in Proc. of the 33rd Annual Hawaii Int.Conf. on system Sciences, vol. 2, 10 pp., Maui, HI, USA, 7-7 Jan. 2000.
[12] E. N. Szynkiewicz, A. Sikora, J. Kołodziej, and P. Szynkiewicz, "Modelling and simulation of secure energy aware fog sensing systems," Simulation Modelling Practice and Theory, vol. 101, Article ID: 102011, May. 2020.
[13] R. Oma, S. Nakamura, D. Duolikun, T. Enokido, and M. Takizawa, "An energy-efficient model for fog computing in the internet of things (IoT)," Internet of Things, vol. 1-2, pp. 14-26, Sept. 2018.
[14] J. Yao and N. Ansari, "Energy-aware task allocation for mobile IoT by online reinforcement learning," in Proc. IEEE Int. Conf. on Communications, 6 pp., Shanghai, China,20-24 May. 2019.
[15] Y. Zou, J. Zhu, and R. Zhang, "Exploiting network cooperation in green wireless communication," IEEE Trans. on Communications, vol. 61, no. 3, pp. 999-1010, Mar. 2013.
[16] A. Hazra, P. Rana, and M. Adhikari, "Fog computing for next-generation Internet of Things: Fundamental, state-of-the-art and research challenges," Computer Science Review, vol. 48, Article ID: 100549, May 2023.
[17] S. Murugesan, "Harnessing green IT: Principles and practices," IT Professional, vol. 10, no. 1, pp. 24-33, Jan./Feb. 2008.
[18] N. Chen, et al., "Spectral graph theory-based virtual network embedding for vehicular fog computing: A deep reinforcement learning architecture," Knowledge-Based Systems, vol. 257, Article ID: 109931, Dec. 2022.
[19] R. Das and M. M. Inuwa, "A review on fog computing: Issues, characteristics, challenges and potential applications," Telematics and Informatics Reports, vol. 10, Article ID: 1100049, Jun. 2023.
[20] G. Anastasi, M. Conti, M. D. Francesco, and A. Passarella, "Energy conservation in wireless sensor networks: A survey," Ad hoc Networks, vol. 7, no. 3, pp. 537-568, May 2009.
[21] K. Verma and A. Kumar, "Rank based mobility-aware scheduling in Fog computing," Informatics in Medicine Unlocked, vol. 24, Article ID: 100619, 2021.
[22] R. Naha and S. Garg, "Multiple linear regression-based energy-aware resource allocation in the fog computing environment," Computer Networks, vol. 216, Article ID: 109240, Oct. 2022.
[23] N. Potu and S. Bhukya, "Quality-aware energy efficient scheduling model for fog computing comprised IoT network," Computers & Electrical Engineering, vol. 97, Article ID: 107603, Jan. 2022.
[24] M. Qin, M. Li, and R. O. Yahya, "Dynamic IoT service placement based on shared parallel architecture in fog-cloud computing," Internet of Things, vol. 23, Article ID: 100856, Oct. 2023.
[25] Y. Sellami, Y. Imine, and A. Gallais, "A verifiable data integrity scheme for distributed data sharing in fog computing architecture," Future Generation Computer Systems, vol. 150, pp. 64-77, Jan. 2024.
[26] H. Sabireen and V. Neelanarayanan, "A review on fog computing: architecture, fog with IoT, algorithms and research challenges," ICT Express, vol. 7, no. 2, pp. 162-176, Jun. 2021.
[27] M. Abbasi, E. M. Pasand, and M.R. Khosravi, "Intelligent workload allocation in IoT–Fog–cloud architecture towards mobile edge computing," Computer Communications, vol. 169, pp. 71-80, Mar. 2021.
[28] A. Ahmad, N. Javaid, M. Imran, M. Guizani, and A. A. Alhamed, "An advanced energy consumption model for terrestrial wireless sensor networks," in Proc. Int. Wireless Communications and Mobile Computing Conf., pp. 790-793, Paphos, Cyprus, 5-9 Sept. 2016.
[29] Y. Zhou, N. Wang, and W. Xiang, "Clustering hierarchy protocol in wireless sensor networks using an improved PSO algorithm," IEEE Access, vol. 5, pp. 2241-2253, 2017.
[30] B. Suresh and S. C. Prasad, "An energy efficient secure routing scheme using LEACH protocol in WSN for IoT networks," Measurement: Sensors, vol. 30, Article ID: 100883, Dec. 2023.
[31] A. M. K. Abdulzahra, A. Kadhum, and M. A. Qurabat, "Optimizing energy consumption in WSN-based IoT using unequal clustering and sleep scheduling methods," Internet of Things,vol. 22, Article ID: 100765, Jul. 2023.
[32] M. V. Babu and C. N. S. Kumar, "AE-LEACH: An incremental clustering approach for reducing the energy consumption in WSN," Microprocessors and Microsystems, vol. 93, Article ID: 104602, Sept. 2022.
[33] S. Wang, J. Yu, M. Atiquzzaman, H. Chen, and L. Ni, "CRPD: a novel clustering routing protocol for dynamic wireless sensor networks," Personal and Ubiquitous Computing, vol. 22, pp. 545-559, 2018.
[34] F. Y. Okay and S. Ozdemir, "Routing in fog-enabled IoT platforms: A survey and an SDN-based solution," IEEE Internet of Things Journal, vol. 5, no. 6, pp. 4871-4889, Dec. 2018.
[35] F. Bajaber and I. Awan, "Adaptive decentralized re-clustering protocol for wireless sensor networks," Journal of Computer and System Sciences, vol. 77, no. 2, pp. 282-292, Mar. 2011.
[36] D. Kumar, T. C. Aseri, and R. Patel, "EEHC: Energy efficient heterogeneous clustered scheme for wireless sensor networks," Computer Communications, vol. 32, no. 4, pp. 662-667, Mar. 2009.
[37] S. Lindsey, C. Raghavendra, and K. M. Sivalingam, "Data gathering algorithms in sensor networks using energy metrics," IEEE Trans. on Parallel and Distributed Systems, vol. 13, no. 9, pp. 924-935, Sept. 2002.
[38] A. A. Suwaili and O. Simeone, "Energy-efficient resource allocation for mobile edge computing-based augmented reality applications," IEEE Wireless Communications Letters, vol. 6, no. 3, pp. 398-401, Jun. 2017.
[39] X. Li, et al., "Adaptive aggregation routing to reduce delay for multi-layer wireless sensor networks," Sensors, vol. 18, no. 4, Article ID: 1216, Apr. 2018.
[40] A. S. M. Sanwar Hosen, et al., "A QoS-aware data collection protocol for LLNs in fog-enabled internet of things," IEEE Trans. on Network and Service Management, vol. 17, no. 1, pp. 430-444, Mar. 2019.