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Abstract
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This research focuses on the data allocation problem (DAP), a critical challenge in computing, especially in cloud and edge environments. As data-intensive applications continue to proliferate, effective resource management becomes essential to optimize performance and minimize costs. This study uses the Whale Optimization Algorithm (WOA), which is inspired by the hunting strategies of sperm whales, as a promising meta-heuristic solution to solve the data allocation problem (DAP). The unique approach of WOA balances exploration and exploitation. and makes it suitable for complex optimization tasks. The DAP was solved by the algorithm (WOA), which was not previously used in the literature Optimization problems are used to measure the efficiency of optimization algorithms. The main goal of this process is to minimize the execution time and transaction costs. The method (WOA) is used to solve this problem The third method is also proposed as a greedy method. The performance of the WOA-based methods in 20 different test problems was investigated. The results showed that the proposed methods are better in terms of execution time and total cost, from the results of the available methods in the literature.
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