@inproceedings{bhagwan2014adtributor,
author = {Bhagwan, Ranjita and Kumar, Rahul and Ramjee, Ramachandran and Varghese, George and Mohapatra, Surjyakanta and Manoharan, Hemanth and Shah, Piyush},
title = {Adtributor: Revenue Debugging in Advertising Systems},
booktitle = {Symposium on Networked Systems Design and Implemenentation (NSDI)},
year = {2014},
month = {April},
abstract = {Advertising (ad) revenue plays a vital role in supporting free websites. When the revenue dips or increases sharply, ad system operators must find and fix the root-cause if actionable, for example, by optimizing infrastructure performance.  Such revenue debugging is analogous to diagnosis and root-cause analysis in the systems literature but is more general.  Failure of infrastructure elements is only one potential cause; a host of other dimensions (e.g., advertiser, device type) can be sources of potential causes. Further, the problem is complicated by derived measures such as costs-per-click that are also tracked along with revenue.
Our paper takes the first systematic look at revenue debugging. Using the concepts of explanatory power, succinctness, and surprise, we propose a new multi-dimensional root cause algorithm for fundamental and derived measures of ad systems to identify the dimension mostly likely to blame.  Further, we implement the attribution algorithm and a visualization interface in a tool called the Adtributor to  help troubleshooters quickly identify potential causes. Based on several case studies on a very large ad system and extensive evaluation, we show that the Adtributor has an accuracy of over 95% and helps cut down troubleshooting time by an order of magnitude.},
publisher = {USENIX},
url = {http://approjects.co.za/?big=en-us/research/publication/adtributor-revenue-debugging-in-advertising-systems/},
edition = {Symposium on Networked Systems Design and Implemenentation (NSDI)},
}