1. Pricing in Computer Network: Reshaping the Research Agenda Authors: S. Shenker, D. Clark, D. Estrin and S. Herzog Presenter: Lihua Yuan Feb 15, 2004, ECS 289L Network Pricing

2. The Authors Scott Shenker: Integrated Service Dave Clark: E2E argument vs. the brave new world Deborah Estrin: Routing Arbitor, VINT S. Herzog: ? The Blind Men and the Elephant

3. Outline Current research – the optimality paradigm Critiques –Is marginal cost relevant? –Accessible? –Is optimality the only goal? New pricing paradigm – Edge Pricing Architecture Issues

4. Current Research Flat pricing <> Usage-based pricing Assume usage-based pricing is necessary Find “optimal” in a simplified model Price  marginal congestion costs

5. Critiques 1 – Is marginal congestion cost relevant? 1.Marginal cost is a function of demand and supply, –marginal cost > facility cost + operation cost ? –Stable competitive equilibrium –Total charge = attachment fee + usage fee 2.Marginal cost could be different from different sub populations of users Every subset has its own utility function Competition aimed at a certain subset? eg. Mobile phone service plans?

6. Critiques 2 – Is Marginal Costs Accessible? Does a simple utility function exist in reality? –E.g. Utility a function of bandwidth or delay, Anybody doing this in real life? Different users  different requirements Per-packet based charge vs. Flow-based utility –Users don’t think at packet level Packet-utility relationship ever changing –Adaptive applications, improved TCP

7. Critique 3 – Is Optimality the Only Goal? Optimality in simplified model  ignored too many basic structural issues Pricing should be compatible with structure of network applications Encourage multicast Charge receiver or sender? Compatible with network service market –Multilateral vs. Bilateral

8. Critique 3 – Is Optimality the Only Goal? Local control more important than absolute optimal –Optimality  single pricing scheme across the network –Locality in pricing –No truly optimal scheme anyway

9. Edge Pricing – Approximating congestion costs 1. Replace the current congestion condition by expected congestion condition  QoS-sensitive time-of-day pricing  Insensitive to instant fluctuation  Not encourage dynamic adaptation, but time- shift  User monitoring and adaptatio (Mobile phone again )  Variability at Edge – Difficult for network to access

10. Edge Pricing – Approximating congestion costs 2.Replace the cost of the actual path with the cost of the expected path Depends only on Source-Destination pair Dependency on routing brings extra dynamics Easier for user to adapt

11. Edge Pricing – Local Determination Prices determined locally at access point (network edge) –Not distributed computed alone the entire path –May depend on information collected from the whole network –Bilateral relationship –Billing structure completely local

12. Edge Pricing – Forms Usage-constraining prices –Two extreme cases Flat rate (up to certain capacity, this assumption often hidden) Per-packet/per-reservation charge

13. Architectural Issues – Multicast AddressPath stability Path graph Receive rs UnicastIDstablelinefixed Multicastlogical name notreevarying Approach 1: identify every receiver Approach 2: compute cost on-the-fly

14. Architectural Issues – Charging Receivers How does a receiver indicate its willingness to pay? –RSVP How to bill the receiver? –At the receiver’s access point –Charges are accumulated along the path

15. Architectural Issues – Open Issues How to charge? –S/D pair (go Dutch?) –multicast price depend on # of audience? Free ride? (A  B  C)

16. Questions? I got one! –Why network engineers need to worry about sender-pay or receiver-pay scheme? Can’t sender bill the receiver later/beforehand?