Abstract
Rapidly changing environments such as robots, sensor networks, or medical services are emerging. To deal with them, DBMS should persist sensor data streams instantaneously. To achieve the purpose, data persisting process must be accelerated. Though write ahead logging (WAL) acceleration is essential for the purpose, only a few researches are conducted.
To accelerate data persisting process, this paper proposes remote WAL with asynchronous checkpointing technique. Furthermore this paper designs and implements it. To evaluate the technique, this paper conducts experiments on an object relational DBMS called KRAFT.
The result of experiments shows that remote WAL overwhelms performance disk based WAL. As for throughput evaluation, best policy shows about 12 times better performance compared with disk based WAL. As for logging time, the policy shows lower than 1000 micro seconds which is the period of motor data acquisition on conventional robots.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Madden, S.R., Franklin, M.J., Hellerstein, J.M., Hong, W.: The Design of an Acquisitional Query Processor for Sensor Networks. In: Proceedings of the 2003 ACM SIGMOD International Conference on Management of Data, pp. 491–502 (2003)
Babcock, B., Babu, S., Datar, M., Motwani, R., Widom, J.: Models and Issues in Data Stream Systems. In: ACM Symposium on Principles of Database Systems (2002)
Imai, M., Narumi, M.: Generating common quality of sense by directed interaction. In: Proceedings of the 12th IEEE International Workshop on Robot and Human Interactive Communication(RO-MAN 2003), pp. 199–204 (2003)
Gray, J., Reuter, A.: Transaction Processing: Concepts and Techniques. Morgan Kaufmann Publishers, San Francisco (1993)
Cha, S.K., Song, C.: P*TIME: Highly Scalable OLTP DBMS for Managing Update-Intensive Stream Workload. In: Proceedings of 30th International Conference on Very Large Data Bases, pp. 1033–1044 (2004)
Hvasshovd, S.-O., Torbjørnsen, Ø., Bratsberg, S.E., Holager, P.: The ClustRa Telecom Database: High Availability, High Throughput, and Real-Time Response. In: Proceedings of the 21th International Conference on Very Large Data Bases, pp. 469–477 (1995)
Kawashima, H., Toyama, M., Imai, M., Anzai, Y.: Providing Persistence for Sensor Streams with Light Neighbor WAL. In: Proceedings of Pacific Rim International Symposium on Dependable Computing (PRDC2002), pp. 257–264 (2002)
Kawashima, H., Imai, M., Anzai, Y.: Improving Freshness of Sensor Data on KRAFT Sensor Database System. In: International Workshop on Multimedia Information Systems, pp. 1–8 (2004)
Mohan, C.: Repeating History Beyond ARIES. In: Proceedings of 25th International Conference on Very Large Data Bases, pp. 1–17 (1999)
Spiro, P.M., Joshi, A.M., Rengarajan, T.K.: Designing an Optimized Transaction Commit Protocol. Digital Technical Journal 3(1), 1–16 (1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Kawashima, H., Imai, M., Anzai, Y. (2006). Providing Persistence for Sensor Data Streams by Remote WAL. In: Tjoa, A.M., Trujillo, J. (eds) Data Warehousing and Knowledge Discovery. DaWaK 2006. Lecture Notes in Computer Science, vol 4081. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11823728_50
Download citation
DOI: https://doi.org/10.1007/11823728_50
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37736-8
Online ISBN: 978-3-540-37737-5
eBook Packages: Computer ScienceComputer Science (R0)