Optimizing Resource Allocation and Load Distribution in Fog-Computing for IoT: A Hybrid Approach for Enhanced Performance

Abstract

Efficient resource allocation and load balancing in fog computing is critical for many IoT application systems. The purpose of this paper is to address challenges of load balancing, bottlenecking, overloading, delaying and distributing the load in fog-based IoT. The study presents a hybrid strategy combining Fog-IoT load balancing resource allocation method using Least Connection and Weighted Round-Robin. The analysis assesses the various types of data transmission using various evaluation metrics including throughput, latency, response time, queuing time, speed and required time. The findings show the methods maintains a reduction of system latency, response time and while improving channel utilization and speed.