* Faculty       * Staff       * Contact       * Institute Directory
* Research Groups      
* Undergraduate       * Graduate       * Institute Admissions: Undergraduate | Graduate      
* Events       * Institute Events      
* Lab Manual       * Institute Computing      
No Menu Selected

* Research

Ph.D. Theses

Architectures for Congestion-Sensi Pricing of Network Services

By Murat Yuksel
Advisor: Shivkumar Kalyanaraman
July 3, 2002

Several adaptive pricing proposals have been made in the last decade for the Internet. Usually, however, those proposals studied optimal strategies and did not focus on implementation issues. We address implementation issues for adaptive pricing over a single differentiated-services (diff-serv) domain. We propose a new adaptive pricing framework Distributed Dynamic Capacity Contracting (Distributed-DCC), which is deployable over diff-serv architecture of the Internet. Essence of Distributed-DCC is to employ edge-to-edge coordination along with techniques for estimation of user incentives (e.g. budget estimation). Particularly, congestion can be detected on an edge-to-edge basis, which enables congestion-sensitive pricing at the edges.

Distributed-DCC is able to provide a range of weighted fairness types (i.e. from max-min to proportional) in rate allocation by using pricing as a tool. The provider can tune a parameter, fairness coefficient, to change fairness of the framework.

To illustrate possibility of congestion-sensitive pricing in the framework, we develop a congestion-sensitive pricing scheme, Edge-to-Edge Pricing (EEP), within the framework. We derive optimal prices for EEP and investigate effects of user's elasticity on these optimal prices.

We also investigate congestion control by pricing, especially in terms of time-scale. We illustrate that control of congestion by pricing requires very small time-scale pricing (i.e. frequent updates to prices), which complicates human involvement into negotiations. To solve this time-scale problem, we propose two pricing architectures: Pricing for Congestion Control (PFCC) and Pricing over Congestion Control (POCC). PFCC uses small time-scale pricing directly for controlling congestion and employs end-placed software/hardware agents which take inputs from human user at large time-scale while negotiating with the provider at small time-scale on behalf of the user. POCC uses an underlying edge-to-edge congestion control mechanism by overlaying pricing on top of it. This way, POCC controls congestion at small time-scales while allowing pricing at time-scales large enough for human involvement. We also illustrate how to adapt Distributed-DCC to these architectures.

* Return to main PhD Theses page