Distributed Supervisory Control: Theory and Applications

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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.