Network Economics

Pricing and economic studies of networks.

Home is where the (fast) Internet is: Flat-rate compatible incentives for reducing peak load

Authors: 
Parminder Chhabra, Nikolaos Laoutaris and Pablo Rodriguez
Published: 
SIGCOMM

This paper looks at a model of reducing peak-rate load by incentivising users to move from peak rate slots to off-peak time periods. It has its roots in their HotNets 2008 paper “Good things come to those who (can) wait”. (Users are granted bandwidth in the off-peak for good behaviour in the on-peak.)

How many tiers? Pricing in the Internet transit market

Authors: 
Vytautas Valancius, Christian Lumezanu, Nick Feamster, Ramesh Johari and Vijay Vazirani
Published: 
SIGCOMM

This paper deals with the problem of ISPs selling contracts to other (customer) ISPs. Transit ISPs implement policies which price traffic by volume or by destination with volume discount and cheaper prices to destinations which cost them less. The paper studies destination based tiered pricing with the idea that ISPs should unbundle traffic and sell pricing in tiers according to destination to maximise profits.

The background section offers a useful taxonomy of current bundles sold by transit ISPs. This arises from discussions with ISPs.

Time-Dependent Internet Pricing

Authors: 
Carlee Joe-Wong, Sangtai Ha and Mung Chiang
Published: 
Internet Technologies and Applications Conference

This paper looks at time-dependent pricing schemes. A day is split into 48 half hour periods indexed by an integer. The system is known as TUBE (Time-dependent Usage-based Broadband-price Engineering). They use a control loop to adapt the prices ISPs charge users in response to changing behaviour.

On the 95 percentile billing method

Authors: 
Xenofontas Dimitropoulos, Paul Hurley, Andreas Kind and Marc Ph. Stoecklin
Published: 
Passive and Active Measurement Conference

This paper describes the commonly used 95-percentile billing method which is often used by ISPs to bill other ISPs. The 95-percentile billing method is as follows:

  • Set a billing rate $y per Mbps (Megabit per second).

  • Take a month of traffic counts for the entity you wish to bill.

  • Split the traffic into equal sized time periods of length T (often 5 minutes).

  • Calculate the mean rate in Mbps for each time period.

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