Energy Aware Effective Task Offloading Mechanism in Fog Computing

Fog computing has emerged as a promising paradigm for extending the capabilities of the cloud closer to the edge of the network, enabling efficient processing and analysis of data generated by Internet of Things (IoT) devices. With the proliferation of resource-constrained IoT devices and the need for real-time and low-latency applications, task offloading has become a critical technique in fog computing to optimize resource utilization and improve overall system performance. Energy consumption is a crucial aspect in fog computing environments due to the limited power resources available at the edge devices. Efficiently managing energy consumption is essential to ensure prolonged device operation and minimize environmental impact. Our proposed work focuses on the research and development of energy-aware task offloading techniques considering the execution time in fog computing. The proposed energy-aware task offloading techniques aim to provide a comprehensive solution for fog computing environments, enabling energy-efficient operation, improved system performance, and enhanced sustainability. We have evaluated our proposed method through experimental simulations and the results shows that our method has a significant effect on task offloading in fog computing environment on reducing the execution time and energy consumption.