Abstract
Modern large distributed applications, such as telecommunication and banking services, need to respond instantly to a huge number of queries within a short period of time. The data-intensive, query-intensive nature makes it necessary to build these applications in a distributed data environment that involves a number of data servers sharing service load. How data is distributed among the servers has a crucial impact on the system response time. This paper introduces two policies that dynamically migrate data in such an environment as the pattern of queries on data changes, and achieve query load balance. One policy is based on a central controller that periodically collects the query load information on all data servers and regulates data migration across the whole system. The other policy lets individual server dynamically selects a partner to migrate data and balance query load in between. Experimental results show that both policies significantly improve system performance in terms of average query response time and fairness, and communication overhead incurred is marginal.
This work is supported by the Cultivation Fund of the Key Scientific and Technical Innovation Project Ministry of Education of China(No.708001), the National ’863’ High-Tech Program of China(No.2007AA01Z191,2006AA01Z230), and the NSFC(Grants 60873062).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Narendran, B., Rangarajan, S., Yajnik, S.: Data distribution algorithms for load balanced fault-tolerant Webaccess. In: Proceedings of The Sixteenth Symposium on Reliable Distributed Systems, pp. 97–106 (1997)
Savio, S.: Approximate Algorithms for Document Placement in Distributed Web Servers. IEEE Transactions on Software Engineering, 100–106 (2004)
Yokota, H., Kanemasa, Y., Miyazaki, J.: Fat-Btree: An Update-Conscious Parallel Directory Structure. In: International Conference on Data Engineering (ICDE), pp. 448–457 (1999)
Lee, M.-L., Kitsuregawa, M., Ooi, B.-C., Tan, K.-L., Mondal, A.: Towards Self-Tuning Data Placement in Parallel Database Systems. In: International Conference on Management of Data (SIGMOD), pp. 225–236 (2000)
Feelifl, H., Kitsuregawa, M., Ooi, B.-C.: A fast convergence technique for online heat-balancing of btree indexed database over shared-nothing parallel systems. In: Ibrahim, M., Küng, J., Revell, N. (eds.) DEXA 2000. LNCS, vol. 1873, pp. 846–858. Springer, Heidelberg (2000)
Watanabe, A., Yokota, H.: Adaptive Lapped Declustering: A Highly Available Data-Placement Method Balancing Access Load and Space Utilization. In: International Conference on Data Engineering (ICDE), pp. 828–839 (2005)
Feldmann, M., Rissen, J.P.: GSM Network Systems and Overall System Integration. Electrical Communication (1993)
Jain, R.: The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley Interscience, Hoboken (1991)
Wang, T., Yang, B., Gao, J., Yang, D.: Effective data distribution and reallocation strategies for fast query response in distributed query-intensive data environments. In: Zhang, Y., Yu, G., Bertino, E., Xu, G. (eds.) APWeb 2008. LNCS, vol. 4976, pp. 548–559. Springer, Heidelberg (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2009 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Wang, T. et al. (2009). Dynamic Data Migration Policies for Query-Intensive Distributed Data Environments. In: Li, Q., Feng, L., Pei, J., Wang, S.X., Zhou, X., Zhu, QM. (eds) Advances in Data and Web Management. APWeb WAIM 2009 2009. Lecture Notes in Computer Science, vol 5446. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00672-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-00672-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00671-5
Online ISBN: 978-3-642-00672-2
eBook Packages: Computer ScienceComputer Science (R0)