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This research introduces three pivotal contributions to address critical challenges in cloud computing load balancing. First, we designed a precise objective function to optimize response time and computational cost, ensuring efficient task assignment within resource limits. Building on this, we proposed a hybrid algorithm, ACOCSA, which intelligently combines Ant Colony Optimization (ACO) and Crow Search Algorithm (CSA). This innovative algorithm leverages the strengths of both techniques, balancing exploration and exploitation to achieve outstanding results. Finally, we implemented and rigorously evaluated ACOCSA, demonstrating its ability to reduce response time, lower costs, and enhance fairness across resources. These contributions collectively represent a practical and scalable solution to improve cloud computing efficiency.
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IEEE/ICACT20250248 Slide.10
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