Paper Contents
Abstract
The rapid evolution of the Internet of Things (IoT), where connected devices continuously generate data, hasprompted the growth of edge systems. This study employscommunication, computational and energy dynamics behind IoT assisted edge-compute paradigm. It explores modelsin terms of task offloading, estimation of energy consumption and optimization of task assignment and scheduling problems. The ultimate goal of the study is to provide deep comprehension of the pitfalls and potential in achieving optimal task scheduling across many distinctentities. The research formulates task assignment and scheduling problems, defining constraints and objectives for designing effective optimization algorithms. The study's experimental evaluation demonstrates the superiority of a collaborative task scheduling scheme over traditional approaches, enhancing task throughput and deadline satisfaction. This research contributes insights to the efficiency and scalability of IoT-assisted edge computing, fostering innovation and progress in the IoT ecosystem.
Copyright
Copyright © 2025 Bandla Siva Ranjani. This is an open access article distributed under the Creative Commons Attribution License.
