Mohammad Maifi Hasan Khan
Jiawei Han
ABSTRACT
This paper presents a tool for uncovering bugs due to interactive complexity in networked sensing applications. Such bugs are not localized to one component that is faulty, but rather result from complex and unexpected interactions between multiple often individually non-faulty components. Moreover, the manifestations of these bugs are often not repeatable, making them particularly hard to find, as the particular sequence of events that invokes the bug may not be easy to reconstruct. Because of the distributed nature of failure scenarios, our tool looks for sequences of events that may be responsible for faulty behavior, as opposed to localized bugs such as a bad pointer in a module. An extensible framework is developed where a front-end collects runtime data logs of the system being debugged and an offline back-end uses frequent discriminative pattern mining to uncover likely causes of failure. We provide a case study of debugging a recent multichannel MAC protocol that was found to exhibit corner cases of poor performance (worse than single channel MAC). The tool helped uncover event sequences that lead to a highly degraded mode of operation. Fixing the problem significantly improved the performance of the protocol.We also provide a detailed analysis of tool overhead in terms of memory requirements and impact on the running application.
- http://www.cs.waikato.ac.nz/ml/weka/.Google Scholar
- R. Agrawal and R. Srikant. Fast algorithms for mining association rules. In Proceedings of the Twentieth International Conference on Very Large Data Bases (VLDB'94), pages 487--499, 1994. Google ScholarDigital Library
- M. K. Aguilera, J. C. Mogul, J. L. Wiener, P. Reynolds, and A. Muthitacharoen. Performance debugging for distributed systems of black boxes. In Proceedings of the nineteenth ACM symposium on Operating systems principles (SOSP'03), pages 74--89, 2003. Bolton Landing, NY, USA. Google ScholarDigital Library
- P. Ballarini and A. Miller. Model checking medium access control for sensor networks. In Proceedings of the 2nd International Symposium On Leveraging Applications of Formal Methods, Verification and Validation (ISOLA'06), pages 255--262, Paphos, Cyprus, November 2006. Google ScholarDigital Library
- P. Bodík, G. Friedman, L. Biewald, H. Levine, G. Candea, K. Patel, G. Tolle, J. Hui, A. Fox, M. I. Jordan, and D. Patterson. Combining visualization and statistical analysis to improve operator confidence and efficiency for failure detection and localization. In Proceedings of the 2nd International Conference on Autonomic Computing(ICAC'05), 2005. Google ScholarDigital Library
- Q. Cao, T. Abdelzaher, J. Stankovic, and T. He. The liteos operating system: Towards unix-like abstractions for wireless sensor networks. In Proceedings of the Seventh International Conference on Information Processing in Sensor Networks (IPSN'08), April 2008. Google ScholarDigital Library
- E. Cheong, J. Liebman, J. Liu, and F. Zhao. Tinygals: a programming model for event-driven embedded systems. In Proceedings of the 2003 ACM symposium on Applied computing (SAC'03), pages 698--704, 2003. Melbourne, Florida. Google ScholarDigital Library
- E. Ertin, A. Arora, R. Ramnath, and M. Nesterenko. Kansei: A testbed for sensing at scale. In Proceedings of the 4th Symposium on Information Processing in Sensor Networks (IPSN/SPOTS track), 2006. Google ScholarDigital Library
- G. D. Fatta, S. Leue, and E. Stegantova. Discriminative pattern mining in software fault detection. In Proceedings of the 3rd international workshop on Software quality assurance (SOQUA '06), pages 62--69, 2006. Google ScholarDigital Library
- E. Frank and I. H. Witten. Generating accurate rule sets without global optimization. In Proceedings of the Fifteenth International Conference on Machine Learning (ICML'98), pages 144--151, 1998. Google ScholarDigital Library
- D. Gay, P. Levis, R. von Behren, M. Welsh, E. Brewer, and D. Culler. The nesc language: A holistic approach to networked embedded systems. In Proceedings of Programming Language Design and Implementation (PLDI'03), pages 1--11, June 2003. Google ScholarDigital Library
- L. Girod, J. Elson, A. Cerpa, T. Stathopoulos, N. Ramanathan, and D. Estrin. Emstar: a software environment for developing and deploying wireless sensor networks. In Proceedings of the annual conference on USENIX Annual Technical Conference (ATEC'04), pages 24--24, Boston, MA, 2004. Google ScholarDigital Library
- Y. Hanna, H. Rajan, and W. Zhang. Slede: Lightweight specification and formal verification of sensor networks protocols. In Proceedings of the First ACM Conference on Wireless Network Security (WiSec), Alexandria, VA, March-April 2008. Google ScholarDigital Library
- M. M. H. Khan, T. Abdelzaher, and K. K. Gupta. Towards diagnostic simulation in sensor networks. In Proceedings of International Conference on Distributed Computing in Sensor Systems (DCOSS), 2008. Greece. Google ScholarDigital Library
- M. M. H. Khan, L. Luo, C. Huang, and T. Abdelzaher. Snts: Sensor network troubleshooting suite. In Proceedings of International Conference on Distributed Computing in Sensor Systems (DCOSS), 2007. Santa Fe, New Mexico, USA.Google ScholarCross Ref
- H. K. Lee, D. Henriksson, and T. Abdelzaher. A practical multi-channel medium access control protocol for wireless sensor networks. In Proceedings of International Conference on Information Processing in Sensor Networks (IPSN'08), St. Louis, Missouri, April 2008. Google ScholarDigital Library
- P. Levis and D. Culler. Mate: a tiny virtual machine for sensor networks. In Proceedings of the 10th international conference on Architectural support for programming languages and operating systems, San Jose, California, October 2002. Google ScholarDigital Library
- P. Levis, N. Lee, M. Welsh, and D. Culler. Tossim: accurate and scalable simulation of entire tinyos applications. In Proceedings of the 1st international conference on Embedded networked sensor systems (SenSys'03), pages 126--137, Los Angeles, California, USA, 2003. Google ScholarDigital Library
- C. Liu, L. Fei, X. Yan, J. Han, and S. P. Midkiff. Statistical debugging: A hypothesis testing-based approach. IEEE Transactions on Software Engineering, 32:831--848, 2006. Google ScholarDigital Library
- C. Liu and J. Han. Failure proximity: a fault localization-based approach. In Proceedings of the 14th ACM SIGSOFT international symposium on Foundations of software engineering (SIGSOFT'06/FSE-14), pages 46--56, 2006. Google ScholarDigital Library
- C. Liu, Z. Lian, and J. Han. How bayesians debug. In Proceedings of the Sixth International Conference on Data Mining (ICDM'06), pages 382--393, December 2006. Google ScholarDigital Library
- C. Liu, X. Yan, L. Fei, J. Han, and S. P. Midkiff. Sober: statistical model-based bug localization. In Proceedings of the 13th ACM SIGSOFT international symposium on Foundations of software engineering (FSE-13), 2005. Lisbon, Portugal. Google ScholarDigital Library
- C. Liu, X. Yan, and J. Han. Mining control ow abnormality for logic error isolation. In Proceedings of 2006 SIAM International Conference on Data Mining (SDM'06), Bethesda, MD, April 2006.Google ScholarCross Ref
- C. Liu, X. Zhang, J. Han, Y. Zhang, and B. K. Bhargava. Failure indexing: A dynamic slicing based approach. In Proceedings of the 2007 IEEE International Conference on Software Maintenance (ICSM'07), Paris, France, October 2007.Google ScholarCross Ref
- L. Luo, T. F. Abdelzaher, T. He, and J. A. Stankovic. Envirosuite: An environmentally immersive programming framework for sensor networks. ACM Transactions on Embedded Computing Systems, 5(3):543--576, 2006. Google ScholarDigital Library
- L. Luo, T. He, G. Zhou, L. Gu, T. Abdelzaher, and J. Stankovic. Achieving Repeatability of Asynchronous Events in Wireless Sensor Networks with EnviroLog. In Proceedings of the 25th IEEE International Conference on Computer Communications (INFOCOM'06), pages 1--14, 2006.Google ScholarCross Ref
- S. R. Madden, M. J. Franklin, J. M. Hellerstein, and W. Hong. Tinydb: an acquisitional query processing system for sensor networks. ACM Transactions on Database Systems, 30(1):122--173, 2005. Google ScholarDigital Library
- P. Olveczky and S. Thorvaldsen. Formal modeling and analysis of wireless sensor network algorithms in real-time maude. In Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS), Rhodes Island, Greece, April 2006.Google ScholarCross Ref
- J. Polley, D. Blazakis, J. McGee, D. Rusk, and J. S. Baras. Atemu: A fine-grained sensor network simulator. In Proceedings of the First International Conference on Sensor and Ad Hoc Communications and Networks (SECON'04), pages 145--152, Santa Clara, CA, October 2004.Google ScholarCross Ref
- N. Ramanathan, K. Chang, R. Kapur, L. Girod, E. Kohler, and D. Estrin. Sympathy for the sensor network debugger. In Proceedings of the 3rd international conference on Embedded networked sensor systems (SenSys'05), pages 255--267, 2005. Google ScholarDigital Library
- R. Szewczyk, J. Polastre, A. Mainwaring, and D. Culler. Lessons from a sensor network expedition. In Proceedings of the First European Workshop on Sensor Networks (EWSN), 2004.Google ScholarCross Ref
- G. Tolle and D. Culler. Design of an application-cooperative management system for wireless sensor networks. In Proceedings of the Second European Workshop on Wireless Sensor Networks (EWSN'05), pages 121--132, Istanbul, Turkey, February 2005.Google ScholarCross Ref
- P. Volgyesi, M. Maroti, S. Dora, E. Osses, and A. Ledeczi. Software composition and verification for sensor networks. Science of Computer Programming, 56(1-2):191--210, 2005. Google ScholarDigital Library
- Y. Wen and R. Wolski. s2 db: A novel simulation-based debugger for sensor network applications. UCSB 2006, 2006-01. Google ScholarDigital Library
- Y. Wen, R. Wolski, and G. Moore. Disens: scalable distributed sensor network simulation. In Proceedings of the 12th ACM SIGPLAN symposium on Principles and practice of parallel programming (PPoPP'07), pages 24--34, 2007. San Jose, California, USA. Google ScholarDigital Library
- G. Werner-Allen, P. Swieskowski, and M. Welsh. Motelab: A wireless sensor network testbed. In Proceedings of the Fourth International Conference on Information Processing in Sensor Networks (IPSN'05), Special Track on Platform Tools and Design Methods for Network Embedded Sensors (SPOTS), pages 483--488, April 2005. Google ScholarDigital Library
- K. Whitehouse, G. Tolle, J. Taneja, C. Sharp, S. Kim, J. Jeong, J. Hui, P. Dutta, and D. Culler. Marionette: Using rpc for interactive development and debugging of wireless embedded networks. In Proceedings of the Fifth International Conference on Information Processing in Sensor Networks: Special Track on Sensor Platform, Tools, and Design Methods for Network Embedded Systems (IPSN/SPOTS), pages 416--423, Nashville, TN, April 2006. Google ScholarDigital Library
- J. Yang, M. L. Soffa, L. Selavo, and K. Whitehouse. Clairvoyant: a comprehensive source-level debugger for wireless sensor networks. In Proceedings of the 5th international conference on Embedded networked sensor systems (SenSys'07), pages 189--203, 2007. Google ScholarDigital Library
Index Terms
- Dustminer: troubleshooting interactive complexity bugs in sensor networks
Recommendations
Troubleshooting interactive complexity bugs in wireless sensor networks using data mining techniques
This article presents a tool for uncovering bugs due to interactive complexity in networked sensing applications. Such bugs are not localized to one component that is faulty, but rather result from complex and unexpected interactions between multiple ...
Adaptive GTS allocation in IEEE 802.15.4 for real-time wireless sensor networks
The IEEE 802.15.4 standard is able to achieve low-power transmissions in low-rate and short-distance Wireless Personal Area Networks (WPANs). It supports a Guaranteed Time Slots (GTSs) allocation mechanism for time-critical and delay-sensitive data ...
Software-only system-level record and replay in wireless sensor networks
IPSN '15: Proceedings of the 14th International Conference on Information Processing in Sensor NetworksWireless sensor networks (WSNs) are plagued by the possibility of bugs manifesting only at deployment. However, debugging deployed WSNs is challenging for several reasons---the remote location of deployed sensor nodes, the non- determinism of execution ...
Comments