An Efficient Sustainable Energy Utilization and Scheduling for Fog Environment Using Glowworm Swarm Optimization
DOI:
https://doi.org/10.26713/cma.v14i5.2688Keywords:
Load balancing, Scheduling, Glowworm swarm optimization, Fog computing, Energy utilization, Power utilization, Energy consumptionAbstract
The primary benefits of fog computing are a considerable reduction in the volume of data sent across the cloud. This, in turn, results in preserving the network bandwidth from being overcrowded. Also, the use of fog computing has a vital role in minimizing Internet and network latencies. However, Fog computing being distributed in nature faces its own challenges. Two of the primary challenges in Fog computing are distributed scheduling and reduced power utilization in a distributed environment. This study addressing these two challenges optimally and efficiently. This paper proposed a novel hybrid approach for enhancing the load balancing and scheduling
process, promoting considerable energy and power consumption. The hybrid approach integrates the Glowworm Swarm Optimization algorithm as the practical functionalities for load balancing and scheduling jobs in Fog Computing Network (FCN). Our proposed GSWOM approach can perform optimized resource allocation, de-allocation, and management. Also, this study proposed FCN which implemented and experimented with in python software to verify the results. The performance of the proposed approach is evaluated by comparing the obtained results with the earlier contemporary works. From the comparison, it has been found that the proposed GSWOM-FCN outperforms other methods. The results indicate stark improvement in energy consumption and significant improvement due to effective and optimal scheduling. The overall jobs assigned percentage was 96.49% in the case of GSWOM, while it was 86.78% for the existing approach. The classification accuracy is obtained by analyzing the Smart grid stability dataset is 97.73%. Thus, the sustainability prediction using FCN is better than others.
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