Energy-Efficient Cloud Architectures for Internet of Things (IoT) Networks: A Sustainable Approach Toward Green Computing and Resource Optimization

Abstract

The exponential growth of the Internet of Things (IoT) has dramatically transformed the way devices interact, communicate, and exchange data in real time. However, the large-scale deployment of IoT systems introduces substantial energy consumption challenges due to continuous data transmission, computation, and storage demands. Cloud computing serves as an efficient platform for managing these massive data volumes, but the conventional cloud architectures often lack energy optimization mechanisms. This paper presents a detailed study on energy-efficient cloud architectures designed to support IoT networks sustainably. It explores innovative strategies such as energy-aware virtualization, dynamic resource scaling, workload migration, and carbon aware scheduling. Furthermore, it highlights architectural models that integrate edge and fog computing to minimize energy wastage, discusses related literature, identifies existing challenges, and outlines future research directions aimed at achieving sustainable IoT-cloud ecosystems.

KEYWORDS: Energy-efficient cloud, IoT networks, sustainable computing, green architecture, edge computing, workload optimization, carbon-aware scheduling.