GreenTask: A Carbon-Aware Scheduling Algorithm  for Enhancing Energy Efficiency in  Edge-Fog Computing System

Author(s)	Prof. Sukanya J
Country	India
Abstract	With the proliferation of edge and fog computing in IoT-based applications, the need for sustainable computing practices has become more critical than ever. This paper proposes a carbon-aware task scheduling algorithm designed to minimize the carbon footprint in edge-fog networks while maintaining system performance. The algorithm dynamically adjusts task scheduling based on real-time carbon intensity and renewable energy availability, optimizing energy consumption and reducing the environmental impact. Through simulation experiments, we compare our approach with traditional scheduling algorithms, showing significant improvements in carbon efficiency without compromising task completion time. Our work paves the way for the adoption of green computing in smart cities and IoT ecosystems, contributing to the global effort to reduce carbon emissions in distributed computing systems.
Keywords	Carbon-aware scheduling, Edge-fog computing, Green task allocation, Sustainable IoT, Energy-latency tradeoff, Renewable-aware computing, Distributed edge intelligence
Field	Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In	Volume 16, Issue 3, July-September 2025
Published On	2025-07-11
DOI	https://doi.org/10.71097/IJSAT.v16.i3.6974
Short DOI	https://doi.org/g9s9vx

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