The goal of this project is to develop new methods to efficiently predict and control
the quality of service seen by heterogeneous users in an integrated services network.
This is critical to the
development of efficient and economically viable large scale high speed networks.
Statistical sharing can be used to gain efficiency, but it introduces uncertainties in the quality of
service seen by users of a network.
Since the uncertainty that arises with statistical sharing is primarily due to queueing
phenomena, this is the projects main focus. Thus, one may view the project as a study on the behavior and
control of queueing networks. Viewed in this larger context, the work
impacts other vitally important research areas, such as flexible manufacturing networks and
transportation networks. However, the project is primarily focused on issues which
arise in a communication context.
The project involves development of techniques for examining end-to-end performance issues, and
the examination of mechanisms for the allocation and scheduling of resources. The mathematical structure of sample paths
is of particular interest. Performance analyses involving both stochastic and non-stochastic models are being
undertaken.
Principal Investigator: R. L. Cruz