Distributed Supervisory Control: Theory and Applications

我们建议发展理论的离散事件系统的分布式监控的背景下，两个应用程序-分布式调试和分布式仿真。 在分布式控制中，以前的大多数工作都是基于控制器不通信的假设。 没有通信能力的控制导致非常严格的行为。最近，有一些重要的工作，将通信纳入分布式控制理论。 Ricker和Rudie将模态逻辑用于监督控制。 巴雷特和拉福琼也解决了沟通的问题。 他们提供了必要和充分的条件，通过沟通的监督控制器（近视和非近视的未来通信的期望）的控制。 虽然这些工作提供了许多见解，但它们在应用于真实的系统时有局限性，例如，它们假设没有通信延迟，并且控制器在系统的初始状态上是同步的。 这些假设是不正确的，在当今的通信网络中，通信延迟在决策中起着重要的作用。 这个项目的目标是消除这些假设，然后将理论应用到一些分布式应用程序中，我们将考虑的第一个应用是调试分布式程序。 分布式调试中的许多问题都可以归结为观察与控制的框架。 虽然分布式程序的观察问题已经被各种研究人员研究，但控制问题却很少受到关注。 自动控制的抽象为用户测试分布式程序提供了强大的功能。 控制消息顺序的能力对于程序员测试具有不同消息和事件顺序的程序是有用的。 类似地，如果分布式程序与外部观察者交互，则不同进程的相对速度可能会影响结果。 在所提出的方法中，系统将自动控制各种进程的速度，使所需的谓词成为true。我们将考虑的第二个应用是分布式仿真。 分布式仿真主要有两种方法-保守和乐观。 最近，我们开发了第三种方法，称为K-乐观算法，它允许在程序执行过程中改变乐观。 我们的假设是，适当的乐观控制，K-乐观算法可以运行速度比保守以及乐观算法。 我们建议开发一个自适应控制算法的分布式仿真和测量其性能相对于传统的algorithm.We注意到，在这里提出的项目需要在离散，事件系统以及分布式系统的监督控制的专业知识。 我们在这两个领域都进行了广泛的工作，该项目的目标之一是从一个学科到另一个学科的思想交叉。

We propose to develop theory of distributed supervisory control of discrete events systems in the context of two applications - distributed debugging and distributed simulation. Most of the previous work in distributed control is based on the assumption that the controllers do not communicate. Control without the ability to communicate leads to very restrictive behavior.Recently, there has been some important work to incorporate communication in the theory of distributed control. Ricker and Rudie have used the modal logic for supervisory control. Barrett and LaFortune have also tackled the problem of communication. They provide necessary and sufficient conditions for control by communicating supervisory controllers (with myopic and non-myopic expectations of future communication). Although these works provides many insights, they have limitations in application to real systems, For example they assume that there are no communication delays and that controllers are synchronized on the initial state of the system. These assumptions are not true in the present day communication networks in which communication delays play an important role in decision making. The objective of the proposed project is to remove such assumptions and then apply the theory to some distributed applications.The first application we will consider is that of debugging distributed programs. Many of the problems in distributed debugging can be cast into the framework of observation and Control. While issues in observation of a distributed program has been studied by various researchers, the issue of control has received less attention. The abstraction of automatic control provides great power to the user while testing a distributed program. The ability to control the message ordering is useful for the programmer to test the program with different message and event ordering. Similarly, if a distributed program is interacting with an external observer, the relative speed of different processes may affect the outcome. In the proposed method, the system will automatically control the speed of various processes so that the desired predicate becomes true.The second application that we will consider is that of distributed simulation. There are primarily two approaches for distributed simulation - conservative and optimistic. Recently, we have developed a third approach called K-optimistic algorithm which allows the optimism to be changed during the execution of the program. Our hypothesis is that with the proper control of optimism, the K-optimistic algorithm can run faster than both conservative as well as optimistic algorithm. We propose to develop an adaptive control algorithm for distributed simulation and measure its performance with respect to traditional algorithms.We note here that the proposed project requires expertise in supervisory control of discrete, event systems as well as distributed systems. We have worked extensively in both of these areas and one of the goals of the project is cross-fertilization of ideas from one discipline to the other.