Adaptive Multi-Tiered Replication for Fault Tolerance in Cloud Computing

Abstract

Cloud computing has emerged as a fundamental paradigm for delivering scalable and reliable services. However, ensuring fault tolerance in dynamic and distributed environments remains a significant challenge. This paper proposes an Adaptive Multi-Tiered Replication (AMTR) framework that enhances fault tolerance through a multi-level replication strategy. By intelligently adapting replication strategies based on workload characteristics and system behaviors, AMTR optimizes resource utilization and enhances service availability. This paper introduces Adaptive Multi-Tiered Replication (AMTR), a novel method designed to enhance fault tolerance in cloud environments. AMTR classifies data into multiple tiers based on criticality, access frequency, and performance requirements, allowing for dynamic adjustment of replication strategies in real-time. By integrating predictive failure analysis, multi-region replication, and energy-efficient techniques, AMTR ensures high availability, minimizes latency, and reduces operational costs. The proposed approach is validated through simulations that demonstrate significant improvements in fault tolerance, resource efficiency, and overall system resilience compared to traditional replication strategies.