Performance Study of Congestion Price
based Adaptive Service
Xin Wang and Henning Schulzrinne
Columbia University
Abstract:
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 congestion-sensitive
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.
