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System Analysis of State-Aware Resource Allocation for Closed-Loop Control Systems

机译:闭环控制系统的状态感知资源分配系统分析

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Wireless closed-loop control is of major significance for different application areas, such as future industrial manufacturing, and ultra-reliable low-latency communications (URLLC) are designed to enable such systems. Static multi-connectivity, in which a number of independent parallel channels are allocated for each service, is a possible solution to achieve URLLC requirements, but this increases resource usage significantly, which becomes an issue particularly in multi-user systems. Building upon a control-communications codesign (CoCoCo) approach, a control-application optimized state-aware resource allocation (SARA) scheme was developed, which exploits the control cycle's inherent capability of tolerating a limited number of consecutive packet losses before ultimately failing. In essence, SARA negatively correlates packet losses through dynamic channel allocation in order to yield extraordinary availability values while keeping the average resource consumption low. This article develops a multi-user system representation of SARA with competition for limited resources using a Markov chain approach and subsequently evaluates the mean time to failure, demonstrating that SARA scales better than static multi-connectivity, fully supporting the maximum system availability at fewer channels per agent.
机译:无线闭环控制对于不同的应用领域具有重要意义,例如未来的工业制造,而超可靠的低延迟通信(URLLC)旨在实现此类系统。静态多连接,其中为每个服务分配了许多独立的并行频道,是实现URLLC要求的可能解决方案,但这显着提高了资源使用,这成为特别是在多用户系统中的问题。在控制通信代码(Cococo)方法上,开发了一种控制应用优化的状态感知资源分配(SARA)方案,该方案利用了控制周期在最终失败之前容忍有限数量的连续分组损耗的固有能力。实质上,SARA通过动态信道分配对数据包损失负相关,以便在保持平均资源消耗的同时产生非凡的可用性值。本文使用Markov链方法对有限资源进行有限资源的竞争,并且随后使用Markov链方法进行竞争,并且展示SARA比静态多连接更好,完全支持较少的频道最大系统可用性每个代理人。

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