Microsoft OLAP solutions
Voice over IP performance monitoring
ACM SIGCOMM Computer Communication Review
Time Series Analysis: Forecasting and Control
Time Series Analysis: Forecasting and Control
iDiff: Informative Summarization of Differences in Multidimensional Aggregates
Data Mining and Knowledge Discovery
Explaining Differences in Multidimensional Aggregates
VLDB '99 Proceedings of the 25th International Conference on Very Large Data Bases
Diamond in the rough: finding Hierarchical Heavy Hitters in multi-dimensional data
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
IP fault localization via risk modeling
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
Automatic misconfiguration troubleshooting with peerpressure
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Using magpie for request extraction and workload modelling
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Towards highly reliable enterprise network services via inference of multi-level dependencies
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
NetPrints: diagnosing home network misconfigurations using shared knowledge
NSDI'09 Proceedings of the 6th USENIX symposium on Networked systems design and implementation
Detailed diagnosis in enterprise networks
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Ganesha: blackBox diagnosis of MapReduce systems
ACM SIGMETRICS Performance Evaluation Review
G-RCA: a generic root cause analysis platform for service quality management in large IP networks
Proceedings of the 6th International COnference
Q-score: proactive service quality assessment in a large IPTV system
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Structured comparative analysis of systems logs to diagnose performance problems
NSDI'12 Proceedings of the 9th USENIX conference on Networked Systems Design and Implementation
Divergence measures based on the Shannon entropy
IEEE Transactions on Information Theory
Measuring and fingerprinting click-spam in ad networks
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
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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.