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Optimizing Energy Consumption through Hybrid Edge-Cloud Computation Models

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Optimizing Energy Consumption through Hybrid Edge-Cloud Computation Models


Awodire, Moyosoluwa | Abrahams, Oluwafemi



Awodire, Moyosoluwa | Abrahams, Oluwafemi "Optimizing Energy Consumption through Hybrid Edge-Cloud Computation Models" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-9 | Issue-6, December 2025, pp.186-194, URL: https://www.ijtsrd.com/papers/ijtsrd98796.pdf

The rapidly increasing number of Internet of Things (IoT) devices is forecast to exceed 75 billion by 2025, driving demand for energy-efficient computing frameworks to support data-intensive applications in emerging technologies such as smart cities, healthcare, and industrial automation. Edge-cloud computing architecture leverages both edge processing capacity and centralized cloud processing capacity to address the inherent limitations of edge processing, namely energy costs associated with limited resources at the edge or transmission costs (including energy and delay) associated with sending data back and forth to the cloud. In this paper, an Energy-Aware Task Offloading (EATO) algorithm is proposed that dynamically offloads tasks to edge devices, edge servers, and the cloud for optimized energy consumption and quality of service (QoS). The EATO algorithm utilizes real-time energy profiling, network conditions, and computational requirements, and is calculated as a mathematical optimization problem. The EATO algorithm was evaluated using a simulation of 100 IoT devices and found to reduce energy consumption by up to 25% compared to edge-only and cloud-only approaches, while producing a 21% enhancement in task scheduling time over state-of-the-art methods [15]. The paper makes two main contributions: a generic, scalable task offloading framework and an examination of hybrid-based architecture for sustainable computing. The findings will encourage researchers to focus on energy efficiency for IoT deployments, and future work will investigate the coordination of these systems with real-world implementations and renewable energy sources.

Edge-cloud computing, energy optimization, task offloading, Internet of Things (IoT), sustainable computing.


IJTSRD98796
Volume-9 | Issue-6, December 2025
186-194
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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