Dynamic load balancing in IoT environments using type-2 fuzzy logic systems

Article type: Research Article

Authors: Rao, Bommaraju Srinivasa^{a; *} | Banerjee, Kakoli^b | Anand Deva Durai, C.^c | Balu, S.^d | Sahoo, Ashok Kumar^e | Priyadharshini, A.^f | Rama Krishna, Paladugu^g | Kakade, Revannath Babanrao^h

Affiliations: [a] Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana | [b] Department of Computer Science and Engineering, JSS Academy of Technical Education, Noida, India | [c] College of Computer Science, King Khalid University, Abha, Saudi Arabia | [d] Department of CSE, KSR Institute for Engineering and Technology, Tiruchengode, Namakkal, Tamilnadu, India | [e] Department of Computer Science and Engineering, Graphic Era Hill University, Dehradun, India | [f] Department of CSE (AIDE), School of CSE, Jain Deemed to be University, Bangalore, India | [g] Department of Computer Science and Engineering, RVR & JCCollege of Engineering, Guntur, Andhra Pradesh, India | [h] Lecturer in Electrical Engineering, Government Residential Women’s Polytechnic Latur, Latur, Maharashtra, India

Correspondence: [*] Corresponding author. Bommaraju Srinivasa Rao, Professor, Department of Computer Science and Engineering, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, Telangana. India. E-mail: [email protected].

Abstract: In recent years, the Internet of Things (IoT) has rapidly emerged as an essential technology, enabling seamless communication between billions of interconnected devices. These devices generate a massive amount of data that requires efficient management to ensure optimum performance in IoT environments. Dynamic load balancing (DLB) is a crucial technique employed to distribute workloads evenly across multiple computing resources, thereby reducing latency and increasing the overall efficiency of IoT networks. This paper presents a novel DLB approach based on type-2 fuzzy logic systems (T2FLS) to enhance the performance and reliability of IoT environments. The proposed T2FLS-based DLB technique addresses the inherent uncertainties and imprecisions in IoT networks by considering various parameters, such as workload, processing capability, and communication latency. A comprehensive performance evaluation is carried out to compare the proposed method with traditional DLB approaches. Simulation results demonstrate that the T2FLS-based DLB technique significantly improves the network’s response time, throughput, and energy efficiency, while also providing better adaptability and robustness to dynamic changes in IoT environments. This study contributes to the advancement of DLB techniques in IoT networks and lays the groundwork for further research in this field.

Keywords: Dynamic load balancing, internet of things, type-2 fuzzy logic systems, performance evaluation, energy efficiency

DOI: 10.3233/JIFS-234105

Journal: Journal of Intelligent & Fuzzy Systems, vol. Pre-press, no. Pre-press, pp. 1-9, 2024