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AI-Driven Predictive Scaling for Multi-Cloud Resource Management: Using Adaptive Forecasting, Cost-Optimization, and Auto-Tuning Algorithms

Year: 2024

Type: article

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.

Source: International Journal of Science and Research (IJSR)

DOI: 10.21275/sr241015062841

Author: Charan Shankar Kummarapurugu

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4403557589

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