Title :
Some tools in modeling complex stochastic systems
Author_Institution :
Dept. of Electr. & Comput. Eng., Massachusetts Univ., Amherst, MA, USA
Abstract :
Sweeping applications of digital computers have dramatically changed the plant that a control engineer faces. Today´s dynamic systems are often based on man-made protocols, driven by discrete events occurring at random times, and are huge in size or dimension. Examples, among many, are communication networks and computing systems. The difficulties for controlling these systems are the lack of analytical models, anarchism in using them (namely every user adds more applications to the system without a global view), and curse of dimensionality. The first step in the control and management of such systems is to develop efficient models so that the system behavior could be quickly evaluated. We have been trying to develop some tools for the modeling of various complex stochastic systems. In this paper we review the key concepts in some of these developments
Keywords :
computer networks; discrete event simulation; discrete event systems; large-scale systems; performance evaluation; queueing theory; stochastic systems; telecommunication control; telecommunication network management; analytical models; complex stochastic systems; dimensionality; dynamic systems; Analytical models; Communication networks; Communication system control; Discrete event simulation; Fluid flow; High-speed networks; Large-scale systems; Stochastic systems; Telecommunication traffic; Traffic control;
Conference_Titel :
Decision and Control, 1997., Proceedings of the 36th IEEE Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4187-2
DOI :
10.1109/CDC.1997.657614
