Stochastic Network Processes.
Abstract
This final report summarizes the publications from our research on stochastic network processes that represent the movement of discrete units in networks. Primary examples are the movement of parts and supplies in manufacturing plants and in distribution systems and the movement of data packets and telephone calls in computer and telecommunications networks. The distinguishing feature of our research was the emphasis on the next generation of intelligent networks that will be the backbone of our manufacturing and computer systems. In these networks, the processing of units at the nodes and the routing of units typically depend dynamically on the actual network congestion, and units move concurrently (e.g. batch processing). Most of the present theory of stochastic network processes is for unintelligent networks in which the nodes operate independently, the routes of units are independent, and the units move one-at-a-time. A recent focus of our network research was on parallel simulation, which is one of the most promising areas for the use of parallel or distributed processing. We developed stochastic network models for assessing the feasibility and quality of various protocols in parallel simulations and we developed algorithms that can be incorporated as subroutines in certain types of parallel processing simulations, such as queueing networks, in which the system evolution can be represented by recursive equations. (AN)
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 28, 1995
- Accession Number
- ADA305674
Entities
People
- Richard F. Serfozo
Organizations
- Georgia Tech