Year: 2024
Type: article
Abstract: This article presents an innovative framework for developing resilient and adaptive artificial intelligence (AI) models specifically designed for real-time analytics in cloud computing environments.The proposed approach introduces a novel Dynamic Learning Rate Adaptation (DLRA) mechanism combined with Cloud-Native Resilience Patterns (CNRP) to create self-adjusting models that maintain high performance under varying workloads.The article implements an Adaptive Performance Enhancement Protocol (APEP) for resource optimization and an Integrity-Preserving Stream Processing (IPSP) mechanism for data consistency.The architecture utilizes microservices with containerization technologies, incorporating a Multi-Stage Recovery Protocol (MSRP) and Dynamic Resource Allocator (DRA) for enhanced system resilience.Experimental
Author: Srinivas Kolluri
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4405799863