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Combining coordination with usage policies to improve mission scheduling resilience

机译:将协调与使用策略结合起来,以提高任务调度的弹性

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Intelligence, surveillance, and reconnaissance (ISR) assets must coordinate to maximize their availability, timeliness, and accuracy of information in a fast-paced, everchanging, and often adversarial environment. The distributed constraint optimization problem (DCOP) is a canonical formulation for representing coordination problems found in the planning and collection phases of global integrated ISR operations. However, ISR assets are often owned by different organizations and have ISR usage policies that dictate additional constraints based on organizational needs. The distributed, agent based system presented in this paper seeks to add resilience to ISR missions by combining DCOP techniques to optimize the scheduling of ISR assets while using policy negotiation to inform the assets??? usage policies in order to increase the number of tasks performed by the system. We overview the system architecture, the coordination protocol, the usage policy engine, and the negotiation strategies used. Broad experimentation shows that use of schedule coordination coupled with policy negotiation outperforms the use of either technique alone.
机译:情报,监视和侦察(ISR)资产必须进行协调,以在快节奏,瞬息万变且经常具有对抗性的环境中最大化其可用性,及时性和信息准确性。分布式约束优化问题(DCOP)是一种典型的表示形式,用于表示在全球集成ISR运营的计划和收集阶段中发现的协调问题。但是,ISR资产通常由不同的组织拥有,并且具有ISR使用策略,这些策略根据组织的需求指示其他约束。本文提出的基于分布式代理的系统旨在通过结合DCOP技术优化ISR资产的调度,同时使用策略协商来通知资产,从而为ISR任务增加弹性。使用策略,以增加系统执行的任务数量。我们概述了系统体系结构,协调协议,使用策略引擎以及所使用的协商策略。广泛的实验表明,将时间表协调与策略协商结合使用优于单独使用这两种技术。

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