Performance Study of Congestion Price based Adaptive Service

In a network with enhancements for QoS support, pricing of network services based on the level of service, usage, and congestion provides a natural and equitable incentive for applications to adapt their sending rates according to network conditions. In this paper, we first propose a dynamic, congestion-sensitive pricing algorithm, and also develop the demand behavior of adaptive users based on a physically reasonable user utility function. We then develop a simulation framework to compare the performance of a network supporting congestion-sensitive pricing and adaptive reservation to that of a network with a static pricing policy. We also study the stability of the dynamic pricing and reservation mechanisms, and the impact of various network control parameters. The results show that the congestionsensitive pricing system takes advantage of application adaptivity to achieve significant gains in network availability, revenue, and user-perceived benefit relative to the fixed-price policy. Congestion-based pricing is stable and effective in limiting utilization to a targeted level. Users with different demand elasticity are seen to share bandwidth fairly, with each user having a bandwidth share proportional to its relative willingness to pay for bandwidth. The results also show that even a small proportion of adaptive users may result in a significant performance benefit and better service for the entire user population both adaptive and non-adaptive users. The performance improvement given by the congestion-based adaptive policy further improves as the network scales and more connections share the resources.