Traditional approaches to network provisioning assume availability of the reliable estimates for the expected demands. This assumption, however, oversimplifies many practical situations when some incomplete information on the expected demands is available, and proper utilization of this information may improve the network performance. In a case of traffic engineering the uncertainty in the expected demands may be a result of sudden changes in the demand pattern, when significant statistical uncertainty in determining the varying demand pattern and possible undesirable transient effects make continuous adjustment of the routing algorithm to varying demands difficult. A long-term network provisioning, e.g., capacity planning, is a subject to uncertainties in the overall economic conditions. Despite the network may be capable of controlling demands through pricing, the overall economic conditions affect the price-demand curve. As the recent sharp downturn in the demand for communication bandwidth demonstrated, making long-term network planning decisions without assessing reliability of the underlying assumptions on the expected demands may lead to disastrous results. Assuming that the expected demand is an unknown mixture of some known scenarios, i.e., demand matrices, this paper proposes a framework for robust network provisioning by guarding against the worst case scenario with respect to the future demands. This framework can be interpreted as a game between the network, e.g., service provider, and nature. The service provider makes the network provisioning decisions in an attempt to minimize losses due to the uncertain future demands, while the nature selects a feasible demand matrix. Solution to this game balances risks of over and under provisioning of the network.
Proceedings of the IEEE International Conference on Communications (ICC 2003)
Network Provisioning as a Game Against Nature, Proceedings of the IEEE International Conference on Communications (ICC 2003), May 11-15, , [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=50725
(Accessed September 26, 2023)