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<p>To systematically guide the orderly computation of vast amounts of eastern data to the west, we proposed an Improved Sparrow Search Algorithm-based Data Resource Scheduling (ISSA-DRS). This strategy utilizes Tent chaotic mapping to initialize the population. It incorporates t-distribution mutation to perturb the positions of discoverers, thereby enhancing the algorithm’s global search and local adjustment performance. Considering constraints such as storage capacity and total transmission delay, we established an objective function to optimize data resource scheduling and maximize efficiency. We validated the performance of the Improved Sparrow Search Algorithm (ISSA) in data resource scheduling by integrating it with the Huawei Software Elite Challenge judge for benefit simulation. Experiments show that ISSA performs better in data resource scheduling and lower delay in the experimental environment. Compared with classical scheduling algorithms, the ISSA effect is improved by 5.02-22.19%.</p>

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Data resource scheduling strategy based on improved sparrow search algorithm

  • 期刊论文

  • 发表日期：

    2025年9月29日

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  • Bin Zhuge,
  • Tingting Pan,
  • Qianye Ren,
  • Zitian Zhang,
  • Ligang Dong,
  • Xian Jiang

摘要

To systematically guide the orderly computation of vast amounts of eastern data to the west, we proposed an Improved Sparrow Search Algorithm-based Data Resource Scheduling (ISSA-DRS). This strategy utilizes Tent chaotic mapping to initialize the population. It incorporates t-distribution mutation to perturb the positions of discoverers, thereby enhancing the algorithm’s global search and local adjustment performance. Considering constraints such as storage capacity and total transmission delay, we established an objective function to optimize data resource scheduling and maximize efficiency. We validated the performance of the Improved Sparrow Search Algorithm (ISSA) in data resource scheduling by integrating it with the Huawei Software Elite Challenge judge for benefit simulation. Experiments show that ISSA performs better in data resource scheduling and lower delay in the experimental environment. Compared with classical scheduling algorithms, the ISSA effect is improved by 5.02-22.19%.