ABSTRACT This paper addresses the issues concerning resource allocation and process scheduling in a dynamic environment, where resources are distributed and availability of them is uncertain. In this context, we introduce a new multi-agent-based resource allocation and process scheduling approach, where agents communicate and cooperate among themselves to produce an optimal schedule. A distributed constraint optimization problem-based model in accordance with Markov Decision Process is proposed in this regard. We overcome the hardship of existing centralized approach and our technique optimizes not only the process completion delay but also the number of resources being idle, which is much more beneficial. Apart from the theoretical approach, we take a case study in its practical application domain to validate our claim. Analysis and experimental results show that this proposed method outperforms the state-of-the-art methods and bridges the gap between theory and its applications.

中文翻译：

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分布式环境中的动态进程调度与资源分配：基于代理的建模与仿真

摘要 本文解决了动态环境中资源分配和进程调度的问题，其中资源是分布式的，它们的可用性是不确定的。在这种情况下，我们引入了一种新的基于多代理的资源分配和进程调度方法，代理之间进行通信和合作以产生最佳调度。对此，提出了一种基于马尔可夫决策过程的分布式约束优化问题模型。我们克服了现有集中式方法的困难，我们的技术不仅优化了流程完成延迟，还优化了空闲资源的数量，这更加有益。除了理论方法外，我们还对其实际应用领域进行了案例研究来验证我们的主张。