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Dynamic Data Optimization in IoT-Assisted Sensor Networks on Cloud Platform

Nguyen A. Tuan1, D. Akila2, Souvik Pal3, Bikramjit Sarkar4, Thien Khai Tran1, G. Mothilal Nehru2, Dac-Nhuong Le5,6,*

1 Faculty of Information Technology, Ho Chi Minh City University of Foreign Languages-Information Technology, Ho Chi Minh City, 70000, Vietnam
2 Department of Information Technology, Vels Institute of Science, Technology & Advanced Studies, Chennai, 600117, India
3 Department of Computer Science and Engineering, Sister Nivedita University, Kolkata, 700156, India
4 Department of Computer Science and Engineering, JIS College of Engineering, Nadia, 741235, India
6 Institute of Research and Development, Duy Tan University, Danang, 550000, Vietnam
7 School of Computer Science, Duy Tan University, Danang, 550000, Vietnam

* Corresponding Author: Dac-Nhuong Le. Email:

(This article belongs to this Special Issue: Future Generation of Artificial Intelligence and Intelligent Internet of Things)

Computers, Materials & Continua 2022, 72(1), 1357-1372.


This article presents a new scheme for dynamic data optimization in IoT (Internet of Things)-assisted sensor networks. The various components of IoT assisted cloud platform are discussed. In addition, a new architecture for IoT assisted sensor networks is presented. Further, a model for data optimization in IoT assisted sensor networks is proposed. A novel Membership inducing Dynamic Data Optimization Membership inducing Dynamic Data Optimization (MIDDO) algorithm for IoT assisted sensor network is proposed in this research. The proposed algorithm considers every node data and utilized membership function for the optimized data allocation. The proposed framework is compared with two stage optimization, dynamic stochastic optimization and sparsity inducing optimization and evaluated in terms of reliability ratio, coverage ratio and sensing error. Data optimization was performed based on the availability of cloud resource, sensor energy, data flow volume and the centroid of each state. It was inferred that the proposed MIDDO algorithm achieves an average performance ratio of 76.55%, reliability ratio of 94.74%, coverage ratio of 85.75% and sensing error of 0.154.


Cite This Article

N. A. Tuan, D. Akila, S. Pal, B. Sarkar, T. Khai Tran et al., "Dynamic data optimization in iot-assisted sensor networks on cloud platform," Computers, Materials & Continua, vol. 72, no.1, pp. 1357–1372, 2022.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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