On-line Optimal Control of a Class of Discrete Event Systems with Real-Time Constraints

We consider Discrete Event Systems (DES) involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. It has been shown that the off-line version of this problem can be efficiently solved by the Critical Task Decomposition Algorithm (CTDA) [16]. In the on-line version, random task characteristics (e.g., arrival times) are not known in adavance. To bypass this difficulty, worst-case analysis may be used. This, however, does not make use of probability distributions and results in an overly conservative solution. In this paper, we develop a new approach which does not rely on worst-case analysis but provides a "best solution in probability" efficiently obtained by estimating the probability distribution of sample-path-optimal solutions. We introduce a condition termed "non-singularity" under which the best solution in probability leads to the on-line optimal control....

• Type: Journal
• Year: 2010
• Where: DEDS
• Authors: Jianfeng Mao, Christos G. Cassandras
• Keywords: DEDS 2010, Distributed And Parallel Computing, Probability Distribution, Task Decomposition Algorithm, Worst-case Analysis