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Disaster Recovery (DR) data centers constitute a critical component of enterprise resilience strategies, yet they remain among the most inefficient elements of modern IT infrastructure, often operating at utilization levels below 5% while incurring substantial capital and operational costs. Traditional DR architectures prioritize redundancy and availability but treat recovery resources as passive insurance assets, resulting in chronic underutilization and limited economic value. This study proposes INTELLI-DR, a comprehensive optimization framework that redefines disaster recovery as an actively utilized, predictive, and economically sustainable system. The framework integrates optimized physical infrastructure, secure multi-tenant isolation, software-defined resource pooling, predictive disaster intelligence, and policy-driven business continuity orchestration. Through large-scale discrete-event simulation encompassing over 10,000 workload scenarios and diverse disaster conditions, as well as pilot implementations across financial services, healthcare, and e-commerce sectors, the proposed approach demonstrates significant performance and economic gains. Results indicate that optimized DR infrastructures can achieve sustained utilization levels of 60–80%, reduce recovery time objectives by approximately 40%, and lower total cost of ownership by 35–50%, while maintaining or improving recovery reliability and compliance. By combining technical innovation with economic and operational considerations, this research challenges conventional DR paradigms and provides a practical roadmap for next-generation resilient infrastructure capable of delivering both robust continuity and measurable business value.
Disaster recovery, infrastructure optimization, predictive failover, resource utilization, cost optimization, business continuity, Data centers.