The problem with P95
I attended a meeting last week with a customer in the Media & Entertainment space, and one of the topics of discussion was that the standard billing method that most ISP's use doesn't work well for their type of business.
The standard billing method that I am referring to is P95, or 95th percentile billing. What we do is measure the input and output traffic on each circuit connected to our routers. Our equipment collects the interface counters every 5 minutes (approximately) and divides the result by the exact number of seconds since the last collection to get the rate. For example, over a 24 hour period you will have about 288 samples for each direction (in/out). We take out the biggest 14 of those samples and then use the remaining largest sample as the billing rate.
Most of the time, this works great. On your typical large ISP traffic trend you'll cut off the very top of the peak providing a good billing rate to traffic volume fit, like this (the red line indicates the P95, the rate at which the customer is billed):

On a content providers circuit this works pretty well too. Even when they have an "event" where they double their traffic due as the result of a new movie trailer release or one of their other providers going down, they don't pay for the traffic unless it's a regular event.

In the media business, or at least certain segments of that space, it is common to see much more erratic traffic patterns, such as a line rate usage for a couple hours out of the day. Doing some reverse calculation, the 14-15 samples in a day that get discarded comes to 75 minutes, and if you transfer a 200 Gig file in the morning on a DS3, assuming 40Mbps throughput, that transfer will take 83 minutes to complete. After throwing away the top 15 samples showing 40Mbps, the 16th sample (which gets used for calculating the monthly bill) is also 40Mbps, so you got charged for 40Mbps of bandwidth even though you only used it for barefly more than an hour each day. The graph below does not perfectly illustrate the situation, but it is a weekly traffic graph from a real media customer of ours in Los Angeles.

There are two potential solutions for this problem.
Option 1) and probably the easiest option is to develop a pricing model that is by the Gigabyte instead of P95 of the rate. Since we know exactly how many Gigabytes are transfered, all we need to do is calculate a price/gig that will yield a more competive rate and remove some of the calculations from the billing and rating algorythm.
Option 2) and much more complicated is to build an event system where the amount of bandwidth can be automatically re-provisioned for the customer either as the result of an XML data input into our customer portal or as the result of some other automatic feedback mechanism such as link threshhold monitoring with an event trigger. Tie that in with automated network provisioning tools, and a billing system that can support a large number of pro-rated bandwidth purchases over a given month.
Why do the more complicated one when you've got an easier solution at your disposal? To solve the specific problem, option 1 is most certainly the way to go, especially in the short term. Option 2 has the advantage of setting the stage for a massive increase in functionality, particularly when it comes to having applications automatically manage how much of a particulary QoS/CoS they need in order to operate properly.
If you've got ideas on how Option 2 might pave the way for you to do some interesting things for your business, drop an idea in our suggestion box by leaving a comment.








