BoosTexter: A Boosting-based Systemfor Text Categorization
Machine Learning - Special issue on information retrieval
Pinpoint: Problem Determination in Large, Dynamic Internet Services
DSN '02 Proceedings of the 2002 International Conference on Dependable Systems and Networks
STRIDER: A Black-box, State-based Approach to Change and Configuration Management and Support
LISA '03 Proceedings of the 17th USENIX conference on System administration
Failure Diagnosis Using Decision Trees
ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Shrink: a tool for failure diagnosis in IP networks
Proceedings of the 2005 ACM SIGCOMM workshop on Mining network data
Automated known problem diagnosis with event traces
Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
IP fault localization via risk modeling
NSDI'05 Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation - Volume 2
OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
Automatic misconfiguration troubleshooting with peerpressure
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
AutoBash: improving configuration management with operating system causality analysis
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
Networkmd: topology inference and failure diagnosis in the last mile
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Automated Rule-Based Diagnosis through a Distributed Monitor System
IEEE Transactions on Dependable and Secure Computing
NetPrints: diagnosing home network misconfigurations using shared knowledge
NSDI'09 Proceedings of the 6th USENIX symposium on Networked systems design and implementation
Towards automated performance diagnosis in a large IPTV network
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Detailed diagnosis in enterprise networks
Proceedings of the ACM SIGCOMM 2009 conference on Data communication
Q-score: proactive service quality assessment in a large IPTV system
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
Proceedings of the 15th Workshop on Mobile Computing Systems and Applications
| Hi-index | 0.00 |
Traditional DSL troubleshooting solutions are reactive, relying mainly on customers to report problems, and tend to be labor-intensive, time consuming, prone to incorrect resolutions and overall can contribute to increased customer dissatisfaction. In this paper, we propose a proactive approach to facilitate troubleshooting customer edge problems and reducing customer tickets. Our system consists of: i) a ticket predictor which predicts future customer tickets; and ii) a trouble locator which helps technicians accelerate the troubleshooting process during field dispatches. Both components infer future tickets and trouble locations based on existing sparse line measurements, and the inference models are constructed automatically using supervised machine learning techniques. We propose several novel techniques to address the operational constraints in DSL networks and to enhance the accuracy of NEVERMIND. Extensive evaluations using an entire year worth of customer tickets and measurement data from a large network show that our method can predict thousands of future customer tickets per week with high accuracy and signifcantly reduce the time and effort for diagnosing these tickets. This is benefcial as it has the effect of both reducing the number of customer care calls and improving customer satisfaction.