Date of Award

Winter 1982

Project Type


Program or Major


Degree Name

Doctor of Philosophy


This thesis presents a methodology for implementing decentralized scheduling for distributed systems. The environment in which the controlling entities make decisions is stochastic and can be described as uncertain since each entity may have a different view of the system state. As a consequence, these entities may make inconsistent decisions.

The methodology is based on defining the system state as a set of distributions and using a queueing model to predict the future behaviour of the system. The predicted state is used to schedule the individual job tasks based on minimum predicted job response time.

A hypothetical real system is simulated. The methodology was tested using different queueing models and under different environments. An evaluation of the proposed technique using the simulation results indicates a consistent performance improvement over the no network case. Suggestions for extending this research are also presented.