Abstract
In sensor networks, a huge amount of data is collected by millions of sensors and small mobile devices need to be processed fast. And database which stores those data always should be able to response for any requirement. Spatial database cluster provides high performance and high availability. That suits sensor networks because spatial database cluster can efficiently manage and process much amount of data. The previous system, however, should write external logs every transaction for high availability in all nodes. So, all of update transactions are slowly processed because of writing external logs. Also, recovery time of the failed node is increased because external logs for all of database are written in only single storage. In this paper, we propose the cluster recovery of spatial database cluster. The proposed method has cluster logs in each table unit for consistency among nodes. Also, the cluster log is written just in case any node is failed. Therefore the proposed method is processed more fast because all update transactions don’t write cluster logs. And the proposed method provides fast recovery because each table can be recovered concurrently.
This research was supported by the MIC(Ministry of Information and Communication), Korea, under the ITRC(Information Technology Research Center) support program supervised by the IITA(Institute of Information Technology Assessment). And this research was supported by the Brain Korea 21 Project in 2007.
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References
Bamford, R., Ahad, R., Pruscino, A.: A Scalable and Highly Available Networked Database Architecture. In: Proceedings of the 25th VLDB Conference, Edinburgh, Scotland (1999)
Bernstein, P.A., Goodman, A.: The Failure and Recovery Problem for Replicated Databases. In: Second ACM Symposium on the Principles of Distributed Computing (1983)
Bonnet, P., Gehrke, J., Mayr, T., Seshadri, P.: Query Processing in a Device Database System. Technical Report: TR99-1775, Cornell University, Ithaca, NY, USA (1999)
Bratsberg, S.E., Hvasshovd, S.O., Torbjornsen, O.: Parallel Solutions in ClustRa. IEEE Computer Society Technical Committe on Data Engineering (1997)
Clifford, C.B.: SYBASE: Replication Server Primer. Computing McGraw-Hill (1995)
Considine, J., Li, F., Kollios, G., Byers, J.: Approximate Aggregation Techniques for Sensor Databases. ICDE (2004)
Hvasshovd, S.O., Torbjornsen, O., Bratsberg, S.E.: The ClustRa Telecom Database: High Availability, High Throughput, and Real-Time Response. In: Proceedings of the 21st VLDB Conference (1995)
Jimenez-Peris, R., Martinez, M.P., Alonso, G.: An Algorithm for Non-Intrusive, Parallel Recovery of Replicated Data and its Correctness. In: IEEE Symp. on Reliable Distributed Systems (2002)
Kemme, B., Alonso, G.: A New Approach to Developing and Implementing Eager Database Replication Protocols. ACM Transactions on Database Systems 25 (2000)
Kemme, B.: Database Replication for Clusters of Workstations. PhD thesis, Department of Computer Science, ETH Zürich, Switzerland (2000)
Koudas, N., Faloutsos, C., Kamel, I.: Declustering spatial databases on a multi-computer architecture (1996)
Lazaridis, I., Mehrotra, S.: Progressive approximate aggregate queries with a multi-resolution tree structure. In: ACM SIGMOD (2001)
Mehta, M., DeWitt, D.J.: Data Placement in Shared-nothing parallel database systems. The VLDB Journal 6 (1997)
Pacitti, E., Minet, P., Simon, E.: Fast algorithms for maintaining replica consistency in lazy master replicated databases. In: Int. Conf. on VLDB, Edinburgh (1999)
Pirahesh, H., Mohan, C., Cheng, J., Liu, T.S., Selinger, P.: Parallelism in Relational Data Base Systems: Architectural Issues and Design Approaches. In: Proceedings Int’l Symp. on Databases in Parallel and Distributed Systems (1990)
Torbjornsen, O., Hvasshovd, S.O., Kim, Y.K.: Towards Real-Time Performance in a Scalable, Continuously Available Telecom DBMS. ClustRa (2001)
Wiesmann, M., Pedone, F., Schiper, A., Kemme, B., Alonso, G.: Understanding Replication in Databases and Distributed Systems. In: Proceedings of the 20th International Conference on Distributed Computing Systems (2000)
You, B.S., Kim, M.G., Kim, J.H., Bae, H.Y.: Design and Implementation of GMS/Cluster. In: Proceedings of the Korea Open GIS Association (2003)
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You, BS., Kim, GB., Bae, HY. (2007). Cluster Recovery for Fault Tolerance of Spatial Database Cluster in Sensor Networks. In: Stojmenovic, I., Thulasiram, R.K., Yang, L.T., Jia, W., Guo, M., de Mello, R.F. (eds) Parallel and Distributed Processing and Applications. ISPA 2007. Lecture Notes in Computer Science, vol 4742. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74742-0_37
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DOI: https://doi.org/10.1007/978-3-540-74742-0_37
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