International Journal of INTELLIGENT SYSTEMS AND APPLICATIONS IN ENGINEERING ISSN:2147-67992147-6 799www.ijisae.org Original Research Paper International Journal of Intelligent Systems and Applications in Engineering IJISAE, 2024, 12(21s), 1045–1051 |1045 Novel Resource Allocation Approach for Fog Computing-Driven IoT Systems Purushottam S. Barve 1 , Dr. Shweta Saxena 2 , Adars U. 3 , N.Venkata Sairam Kumar 4 , Dr. Sachin S. Pund 5 , Dr. Sheela Upendra 6 Submitted: 05/02/2024 Revised: 13/03/2024 Accepted: 19/03/2024 Abstract: Fog computing (FC) has the potential to lower latency and boost speed. Internet of Things (IoT) networks have difficulties allocating resources efficiently. The approaches used are flexible, scalable, or optimized. To maximize performance indicators, new approaches that utilize real-time information, workload sequences, device accessibility and network circumstances are required. We investigate the allocation of resources and task scheduling for numerous devices in IoT systems in this research. IoT devices must properly choose which data to offload to FC nodes (FCNs) as they acquire enormous amounts of data. To tackle the problem of supporting multiple device connections and facilitating fast data transfers with constrained resources, we suggest executing non- orthogonal multiple access (NOMA). Several devices can simultaneously send data spanning time, frequency and coding domains to an identical FCN because of NOMA. Together, we optimize power transmission and resource assignment for IoT devices, meeting QoS requirements and reducing network energy usage. In this research, a unique boosted atom search optimization (BASO) method is presented to tackle it because it is an NP-hard issue. According to the simulation results, the suggested strategy outperforms in terms of greatest throughput, minimum latency and optimal energy use. Keywords: Fog computing (FC), Internet of Things (IoT), resource allocation, energy usage, boosted atom search optimization (BASO) 1. Introduction Fog computing (FC) is complicated and dynamic, making resource allocation (RA) difficult in smart environments and particularly in the IoT. As user demands evolve, resource allocation and management must become more dependable. Systems for managing and allocating resources effectively must be built to adapt the changing demands of its users [1]. Not all fog-specific software is executed by fog devices. The lack of wireless connectivity, device autonomy and centralized management in the fog environment might result in resource and connection problems. In response to the increased need for processing, network and storage capacity to be expanded nearby to end users, FC has emerged as a possible alternative that can complement cloud computing fragility [2]. Since this is a new paradigm, there are a number of outstanding research problems and obstacles to be solved. One of these difficulties is allocating computational resources, which attempts to give the service or application the resources it needs to meet the specified performance and Quality of Service (QoS) metrics acceptably [3]. Using the processing power of fog devices, the FC environment is a state-of-the- art processing architecture that enables application services to be delivered to clients faster and more effectively. Certain convergent-structured devices can function as fog nodes (FNs), providing users with networking, computation and storage capabilities [4]. The shape, structure and functionality of convergent structured devices are different from those of classical computational devices. The dominant use of dynamic contexts, similar to the IoT, in a FC environment, can result in unpredictable events, like high response times, decreased reliability and unavailability of services, when combined with intense competition for limited computational resources [5]. Utilizing RA techniques from other computational paradigms, such as cloud computing, is not without its challenges. It is critical to comprehend the suggestions that have been made and the obstacles that need to be conquered [6]. In FC, different edge nodes can cooperate to share interactions, hiding and processing assets to do 1Assistant Professor, Department of Mechanical Engineering, Yeshwantrao Chawan College of Engineering , Nagpur, Maharashtra, India. Mail id: purubarve5@gmail.com, https://orcid.org/0000-0002-0835- 1433 2Associate Professor, Amity Business School, Amity University Madhya Pradesh, Gwalior, Madhya Pradesh, India. er.saxenashweta15@gmail.com 3Research Scholar, Electronics Department, VMKVEC Salem, Tamil Nadu, India. adars.u@gmail.com 4Associate Professor, Civil Engineering, R.V.R & J.C College of Engineering, Guntur, India. sairam852@gmail.com, 0000-0003-2824-0367 5Assistant Professor, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India. pundss@rknec.edu, https://orcid.org/0000-0002-5616-2469 6symbiosis International Deemed University, Lavale, Pune, India sheelaupendra@scon.edu.in