1. Internet Infrastructure and Pricing

2. Internet Pipelines Technology of the internet enables ecommerce –Issues of congestion and peak-load pricing –Convergence of technology and elimination of boundaries between different communications services Telephone Cable Satellite Wireless ISPs –We will examine pricing policies for this infrastructure and associated issues of economic efficiency

3. Internet Network Architecture End Users Local Area Networks Regional Networks Backbone Networks Other Local Networks Other Regional Networks

4. Congestion Network Economics –Large networks are expensive to build, but cheap to operate –Since fixed costs are sunk costs, network operators have incentives to connect as many users (at very low marginal cost) to the network –As the number of users increases, peak use congestion will occur “World Wide Wait” “Hourglass fatigue –The system then rations the network resource (bandwidth) according to user patience rather than social value

5. Congestion Current efforts to fix the problem –Engineering fixes Expand capacity Doomed to failure: Growth in demand will keep pace with growth in capacity for the foreseeable future Added problem of misallocation of investment resources in response to inefficient use of network resources –Priority schemes IPv6 will include priority settings to move the network away from the current best-effort, first-come-first-served approach to managing traffic Not incentive compatible, however; users can modify the settings to boost their own priority

6. Congestion Digital tragedy of the commons –Congestion imposes external costs on internet users, leading to misallocation of resources Public good aspect of the network –Large fixed cost –Zero marginal cost of adding additional packets during slack periods –Positive social costs of adding packets during congested periods –Highway analogy

7. Pricing Dynamic optimal pricing (Gupta, Stahl and Whinston) –Studies based on simulations show the feasibility of computing accurate, real-time estimates of social costs of congestion –These cost estimates are then combined with information about traffic flow through a site, packet sizes, and priority class of the site to derive optimal prices (=marginal social cost of processing an additional packet) –Users establish a preference profile based on a menu of options including Monetary costs of using the site during peak periods for the specified option Expected waiting times during peak periods for the option

8. Pricing –Smart agents can then automate the user’s decision process based on the established preference profile, using information updates provide by the user’s ISP –Billing is then based on a standard model of wholesale billing practices: User receives bill from ISP for all internet transport services ISP receives a bill from regional network provider and passes individual user costs on to them –Benefits in simulations of various pricing policies

9. Pricing

10. Static priority pricing –Service discipline: Mechanism to allow network operators to assign jobs to specific service classes –Different service classes are priced differently according to user values for each type of service and average resulting congestion on the network –Scheme maximizes time-averaged user benefits –Problems with implementation Requires that operator be able to collect proprietary information about user preferences and valuations of each type of service Users have incentives to misrepresent valuations Static implementation means high-priority users will pay too little during peak periods

11. Pricing Smart Markets –Real-time auctions by packets traversing the network for router or other network services –Encode bids in packet headers –Run uniform auctions over a pre-specified time interval, with the n highest bidding packets being processed in the interval, and charged the n+1 st highest price. If all packets process in the allotted time, the price is zero.

12. Pricing –Problems with the scheme Deadweight time loss while packets are sorted according to bids Efficiency properties of the auction mechanism require –All potential users are present at the auction –The value of a job is not contingent on what happens at other market nodes These properties are violated in dynamic networks –Market operates over time intervals, so packets arriving late (even nanoseconds late) can have no influence on the price, and hence on the allocation of the scarce resource –In real internet operations, the value of having a job processed depends on having all of the relevant packets processed, so that in principle, prices should depend on valuations attached to other packets in a job, and hence, on prices at other smart market nodes in the network

13. Pricing Connection only and flat rate pricing –Dominant form of pricing currently –Connection only fees may vary according to bandwidth option selected, but make no attempt to price for load –Some online services charge per unit of time connected, though these tend to be for dial-up modem connections, as opposed to always-on connection (DSL, cable) –Flat rate pricing charges a single rate for connection regardless of time used AOL’s early experience Serious congestion effects when prices are too low Possibility of using flat rates to implement averaged optimal prices

14. Pricing Policy issues –Imposition of optimal pricing requires some centralized regulation of the network in order to internalize the costs of congestion –Current climate is one of privatization –Likely outcome: Excess investment in engineering solutions: expanded bandwidth distributed uniformly throughout the network Continued congestion effects as demand for bandwidth increases –Possibility for rational pricing on intranets