Integration of Cryptography in Hybrid Fog and Cloud: Balancing Energy Use and Performance for the Best Services
Divya Mishra and Sanjive Tyagi
The integration of fog and cloud computing has emerged as a promising approach to address the challenges of data processing and storage in modern computing environments. This study explores the potential of hybrid fog and cloud integration to balance performance and energy consumption, ensuring optimal services for end-users. This study addresses the limitations of traditional cloud virtual machine (VM) scheduling methods by proposing a novel VM scheduling algorithm that utilizes historical VM resource usage data. The algorithm optimizes VM placement based on performance metrics derived from K-nearest neighbors (KNN) and Naive Bayes classification techniques, ensuring that VMs are placed on the most suitable physical machines. Additionally, it addresses resource contention among VMs by maximizing real CPU utilization, mitigating performance bottlenecks. Experimental results demonstrate the effectiveness of this solution in refining traditional instant-based physical machine selection methods, resulting in improved overall performance and resource efficiency. The proposed algorithm adapts to system dynamics over time, offering potential benefits in terms of cost savings and scalability by reducing the number of physical machines required for deployment.
Keywords: Cryptography, cloud data center, virtual machine, energy consumption, resource management, task scheduling