A Two-Phase Fault Tolerant System to Reduce the Service Level Agreement Violations
A FAULT TOLERANT SYSTEM FOR SLA REDUCTION
DOI:
https://doi.org/10.56042/jsir.v83i12.7568Keywords:
Cloud computing, Fault detection, Machine learning, Scheduling, Service level violationAbstract
Fault-tolerant systems are crucial in environments where uninterrupted service is mandatory and also in environments where continuous service is critical, such as in cloud computing and high-availability systems. The main goal of this research is to introduce a fault-tolerant framework that can effectively manage faults without leading to system failures, ensuring seamless service delivery. The proposed system follows a two-phase approach, incorporating fault detection and correction mechanisms that are designed to maintain system integrity and minimize performance degradation. Upon identifying a fault, the system deploys a correction technique aimed at preventing Service Level Violations (SLV), which could otherwise disrupt the service and breach Service Level Agreements (SLA). This fault-handling process is designed to mitigate interruptions while enhancing overall system performance. The proposed solution demonstrates a significant improvement in reducing SLA violations, achieving a reduction to 98.76%. Additionally, the efficiency of the system is enhanced through an increase in the task success rate, further ensuring the reliability of service. To validate its effectiveness, the performance of this fault-tolerant system has been benchmarked against other contemporary algorithms such as First Come First Serve (FCFS), Priority-based, and CD algorithms. The results reveal that the proposed approach offers notable improvements in response times, reducing them by 23%, 16%, and 33.1% respectively, in comparison to the FCFS, Priority-based, and CD algorithms. These results demonstrate the system's superior capability in handling faults and maintaining service quality, making it an ideal choice for environments where uninterrupted service is mandatory.