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International Journal Of Electrical, Electronics And Computers(IJEEC)

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  3. Vol-10,Issue-6, November - December 2025
  4. Intelligent Performance Optimization Strategies for High-Volume Cloud Storage Infrastructures

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Intelligent Performance Optimization Strategies for High-Volume Cloud Storage Infrastructures

Saad Ahmed


International Journal of Electrical, Electronics and Computers (IJECC), Vol-10,Issue-6, November - December 2025, Pages 7-16, 10.22161/eec.106.2

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Article Info: Received: 27 Oct 2025; Accepted: 25 Nov 2025; Date of Publication: 05 Dec 2025

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The exponential growth of digital data has made high-volume cloud storage a critical component of modern computing ecosystems. Traditional performance optimization techniques, such as static provisioning and manual tuning, struggle to address the complexity, dynamism, and scale of contemporary storage infrastructures. This study investigates intelligent performance optimization strategies, including adaptive caching, workload-aware chunking, dynamic replication, load balancing, and AI/ML-based tuning, to enhance throughput, reduce latency, improve storage utilization, and minimize operational costs. Using a mixed-method research design, experiments were conducted on both simulated and real-world distributed cloud storage environments across varying workloads. Results indicate that intelligent optimization significantly improves system performance: throughput increased from 450 MB/s to 620 MB/s, latency decreased from 120 ms to 85 ms, and storage utilization improved from 70% to 85% under combined strategies. Cost efficiency and reliability also showed marked improvements, with per-GB cost reducing from $0.12 to $0.075, IOPS cost from $0.0025 to $0.0016, and recovery times from 12 minutes to 4 minutes. Workload-specific analyses confirmed the scalability of these strategies across light, moderate, and heavy workloads. Visualization through line charts and heatmaps highlighted balanced resource utilization and efficient workload distribution, demonstrating the transformative potential of intelligent performance optimization in high-volume cloud storage systems.

Intelligent optimization, adaptive caching, dynamic replication, throughput enhancement, cost efficiency.

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