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Research Paper | Computer Science | United States of America | Volume 13 Issue 10, October 2024 | Rating: 6.4 / 10
AI-Driven Predictive Scaling for Multi-Cloud Resource Management: Using Adaptive Forecasting, Cost-Optimization, and Auto-Tuning Algorithms
Charan Shankar Kummarapurugu
Abstract: Serverless computing has revolutionized cloud infrastructure by enabling application development without managing underlying servers. However, integrating serverless with multi-cloud environments introduces unique security and scaling challenges. This paper presents an AI-driven predictive scaling approach using three key algorithms: Adaptive Forecasting Algorithm (AFA), Cost-Optimized Resource Allocation Algorithm (CORA), and AI-Based Auto-Tuning Algorithm (AITA). These algorithms address the challenges of workload prediction, resource optimization, and performance tuning. Experimental results demonstrate significant cost reductions and performance improvements compared to conventional methods.
Keywords: Serverless computing, multi-cloud, predictive scaling, AI algorithms, cost optimization, performance tuning
Edition: Volume 13 Issue 10, October 2024,
Pages: 1164 - 1167