Energy-Optimized Multi-Cloud Deployments for Real-Time Event Systems
Main Article Content
Abstract
The rising demand for real-time event systems, including stock exchanges, emergency response platforms, and IoT-based monitoring, has led to the increased utilization of cloud infrastructures. These deployments often span multiple cloud platforms, which introduces complexities in energy management. Unoptimized multi-cloud environments can result in excessive energy consumption, impacting operational costs and environmental sustainability. This study explores a novel energy-optimization framework for multi-cloud deployments of real-time event systems. By leveraging predictive algorithms, workload orchestration, and dynamic scaling, the framework achieves substantial reductions in energy consumption without compromising system performance. Experimental results demonstrate a 25% reduction in energy usage, a 12.5% improvement in latency, and sustained throughput across optimized deployments. This paper offers actionable insights for organizations seeking to balance efficiency and sustainability in real-time operations
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• Author : Harshita Cherukuri1, Villa 188, My Home Ankura, Sector B, Radial Road-7, Exit No 2, Tellapur, Cyberabad-sangareddy, 502032, Telangana, India , Dr. Bhawna Goel , Dr. Poornima Tyagi
• DOI LINK : 10.56726/IRJMETS60903 doi 10.56726/IRJMETS60903"
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