A Strategy for Implementing Smart Market Pricing Scheme on Diff-Serv

1. A Strategy for Implementing Smart Market Pricing Scheme on Diff-Serv Murat Yuksel and Shivkumar Kalyanaraman Rensselaer Polytechnic Institute, Troy, NY yuksem@rpi.edu, shivkuma@ecse.rpi.edu

2. Outline • Literature development : • congestion-sensitive pricing • the Smart Market (SM) pricing scheme • Adaptation of SM to diff-serv • Simulation experiments • Summary

3. Congestion-Sensitive Pricing • Increase the price when congestion, decrease when no congestion. • A way of controlling user’s traffic demand and hence, a way of controlling network congestion • Better resource (bandwidth) allocation • Fairness • Problems: • Users don’t like price fluctuations! • Each price change must be fed back to the user before it could be applied, i.e. hard to implement in a wide area network.

4. The Smart Market (SM) • Proposed by MacKie-Mason and Varian in 1993 • A congestion-sensitive pricing scheme • Price-per-packet reflecting congestion costs • Users make auction by assigning a “bid” value to each packet before sending it into the network. • The routers maintain a threshold (cutoff) value and pass the packets with bids larger than the threshold. They give priority to the packets with higher bid! • The cutoff value changes dynamically based on local congestion

5. The Smart Market (SM) (cont’d) • The price for each packet is the highest cutoff value it passed through, i.e. market-clearing price. • Why is SM important? • The first congestion-sensitive pricing scheme • Designed for the smallest granularity level (i.e. packet) and hence, attempts the highest possible congestion-sensitivity for network pricing • Ideal scheme from an economic perspective because of its pure congestion-sensitivity

6. Adaptation to Diff-Serv • For data plane packets: • Edge routers (ERs): • write the bid value (b) to the packet header • and then send the packet into the core • Interior Routers (IRs): • maintain a priority queue, sorted according to packets’ bids • if b<T, drop the packet • if b>=T, update the packet’s clearing-price field and forward it • For control plane packets: • ERs and IRs maintain a time interval (τ) which is greater than round-trip time (RTT) to operate. • Hence, the customers are fed back with the current price and their account information at every τ.

7. Adaptation to Diff-Serv (cont’d) • ERs and customers: • Ingress-ER sends a “probe” packet to the network core at every τ to find out the current clearing-price of the network. • Egress-ER responds to the probe packet by a “feedback” packet that includes current clearing-price and bill to the customer. • set the bids of control packets to the maximum bid value (limitation-- bids must be bound to a range) • Ingress-ER informs the customer about his bill and the current clearing-price. • Customers adjust their bids and traffic based upon the bill, the clearing-price, and their utility. • IRs: • update the threshold (T) value at every τ • update control packets’ clearing-price field too

8. Cutoff Value, T • SM says that the IRs should adjust the cutoff value such that T = n/K * D’(Y), where n is the number of customers and K is the capacity of the network. • IRs update T by calculating D’(Y) at the end of each interval, τ. • We used the following approximation for calculating T: where D[i] is the average delay at interval i, and T[i] is the cutoff value for interval i.

9. Simulation Experiments • Packet size is 1000bytes. • Propagation delay is 0.1ms on bottleneck links and 10ms on the others. • RTT is 24ms. • The time interval τ is 1000ms. • User utility is concave: u(x) = w log(x) • Users have a budget w and maximize their surplus by sending at a rate w/p. • We simulated two versions of SM: • SM-SORTED: higher bids have priority at IRs • SM-FIFO: first-come first served

10. Simulation Experiments (cont’d) • 3 user flows with budgets 100, 75 and 25 $/Mb. • Total simulation time is 3000s.

11. Simulation Experiments (cont’d)

12. Simulation Experiments (cont’d)

13. Simulation Experiments (cont’d) • To observe service differentiation: • Two flows with a varying ratio of budgets.

14. Simulation Experiments (cont’d) • Each user flow has a budget of 10$/Mb.

15. Simulation Experiments (cont’d)

16. Summary • Major changes to SM are need for an implementation on diff-serv • By extensive simulation we observed that: • SM can control congestion with low queues and high utilization • Packet sorting (i.e. priority to higher bids) degrades system performance • SM performs in between max-min and proportional fairness