Open Access

ARTICLE

Improved DHOA-Fuzzy Based Load Scheduling in IoT Cloud Environment

R. Joshua Samuel Raj¹, V. Ilango², Prince Thomas³, V. R. Uma⁴, Fahd N. Al-Wesabi^5,6,*, Radwa Marzouk⁷, Anwer Mustafa Hilal⁸

1 Department of Information Science & Engineering, CMR Institute of Technology, Bengaluru, 560037, India
2 Department of Computer Application, CMR Institute of Technology, Bangalore, 560037, India
3 School of Computing, Woldia Institute of Technology, Woldia University, Ethiopia
4 Department of Commerce, School of Commerce, Finance and Accountancy, Christ University, Bangalore, 560029, India
5 Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Saudi Arabia
6 Faculty of Computer and IT, Sana'a University, Yemen
7 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah Bint Abdulrahman University, Saudi Arabia
8 Department of Computer and Self Development, Preparatory Year Deanship, Prince Sattam bin Abdulaziz University, Alkharj, Saudi Arabia

* Corresponding Author: Fahd N. Al-Wesabi. Email:

Computers, Materials & Continua 2022, 71(2), 4101-4114. https://doi.org/10.32604/cmc.2022.022063

Received 26 July 2021; Accepted 26 August 2021; Issue published 07 December 2021

Abstract

Internet of things (IoT) has been significantly raised owing to the development of broadband access network, machine learning (ML), big data analytics (BDA), cloud computing (CC), and so on. The development of IoT technologies has resulted in a massive quantity of data due to the existence of several people linking through distinct physical components, indicating the status of the CC environment. In the IoT, load scheduling is realistic technique in distinct data center to guarantee the network suitability by falling the computer hardware and software catastrophe and with right utilize of resource. The ideal load balancer improves many factors of Quality of Service (QoS) like resource performance, scalability, response time, error tolerance, and efficiency. The scholar is assumed as load scheduling a vital problem in IoT environment. There are many techniques accessible to load scheduling in IoT environments. With this motivation, this paper presents an improved deer hunting optimization algorithm with Type II fuzzy logic (IDHOA-T2F) model for load scheduling in IoT environment. The goal of the IDHOA-T2F is to diminish the energy utilization of integrated circuit of IoT node and enhance the load scheduling in IoT environments. The IDHOA technique is derived by integrating the concepts of Nelder Mead (NM) with the DHOA. The proposed model also synthesized the T2L based on fuzzy logic (FL) systems to counterbalance the load distribution. The proposed model finds useful to improve the efficiency of IoT system. For validating the enhanced load scheduling performance of the IDHOA-T2F technique, a series of simulations take place to highlight the improved performance. The experimental outcomes demonstrate the capable outcome of the IDHOA-T2F technique over the recent techniques.

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Keywords

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