Predictive data mining: a practical guide
Predictive data mining: a practical guide
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Principles of data mining
Computer
Directed diffusion for wireless sensor networking
IEEE/ACM Transactions on Networking (TON)
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Exploratory Data Mining and Data Cleaning
Exploratory Data Mining and Data Cleaning
Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach
IEEE Transactions on Knowledge and Data Engineering
Data Mining with SQL Server 2005
Data Mining with SQL Server 2005
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Frequent pattern mining: current status and future directions
Data Mining and Knowledge Discovery
A Practical Multi-channel Media Access Control Protocol for Wireless Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
The LiteOS Operating System: Towards Unix-Like Abstractions for Wireless Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Towards Diagnostic Simulation in Sensor Networks
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Dustminer: troubleshooting interactive complexity bugs in sensor networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
SNTS: sensor network troubleshooting suite
DCOSS'07 Proceedings of the 3rd IEEE international conference on Distributed computing in sensor systems
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Sensor networks and pervasive computing systems intimately combine computation, communication and interactions with the physical world, thus increasing the complexity of the development effort, violating communication protocol layering, and making traditional network diagnostics and debugging less effective at catching problems. Tighter coupling between communication, computation, and interaction with the physical world is likely to be an increasing trend in emerging edge networks and pervasive systems. This paper reviews recent tools developed by the authors to understand the root causes of complex interaction bugs in edge network systems that combine computation, communication and sensing. We concern ourselves with automated failure diagnosis in the face of non-reproducible behavior, high interactive complexity, and resource constraints. Several examples are given to finding bugs in real sensor network code using the tools developed, demonstrating the efficacy of the approach.