Özet:

Abstract Fault tolerance is critical in constructing robust cloud computing systems to ensure uninterrupted service delivery and maintain economic benefits despite potential faults. This paper presents a novel layered modeling architecture that combines reactive and proactive fault modeling theories to enable reliable, survivable cloud-based applications by addressing fault tolerance concerns. This paper examines the issues of dynamic fault tolerance management and virtual machine (VM) migration in cloud data centers. We introduce a comprehensive algorithm that efficiently manages fault tolerance through proactive measures by leveraging a layered modeling architecture. The algorithm considers defect prediction and resource allocation techniques to minimize service interruptions and maximize resource utilization. It incorporates reactive and proactive fault modeling to identify and respond to faults, anticipates potential faults, and takes preventative measures. This integration makes the cloud computing environment more robust and reliable. However, extensive simulations and evaluations demonstrate the proposed algorithm's effectiveness in reducing service downtime, ensuring application reliability, and sustaining optimal performance. The algorithm's ability to dynamically migrate virtual machines (VMs) based on defect prediction contributes to efficient resource allocation and load balancing, mitigating potential bottlenecks and enhancing system resilience. The results demonstrate the applicability and effectiveness of the proposed framework for maintaining cloud-based applications' dependability. Combining reactive and proactive fault modeling theories, the proposed algorithm provides a comprehensive method for keeping cloud-based applications reliable and fault-tolerant.

Anahtar Kelimeler: