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广域分布式计算环境可提供大规模的计算和存储资源，是支持算力互联和数据流转的重要基础设施。在广域分布式计算环境中，任务与资源的匹配对于提高系统性能具有重要意义。然而，任务与资源的多样性、地理位置分散的资源会增加二者匹配的复杂性。针对响应延迟高、匹配效率低等问题，提出了面向广域分布式计算环境的任务与资源动态匹配方法，通过建立统一的任务需求模型和资源能力模型来简化匹配过程，降低响应延迟。此外，定义了任务向匹配度和资源向匹配度以刻画任务视角和资源视角的偏好，并权衡二者；定义了任务和资源的双向综合匹配度以量化任务需求和资源能力的适配程度。最后通过动态计算每一组任务与资源间的双向综合匹配度以优化匹配效果。实验结果表明，与现有的方法相比，该方法可提升匹配效果，并大幅降低平均响应延迟。

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