CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Cost Efficient Query Optimization in Mobile Environment

by Reena Kasana, Saurabh Sharma
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 120 - Number 22
Year of Publication: 2015
Authors: Reena Kasana, Saurabh Sharma
10.5120/21394-4443

Reena Kasana, Saurabh Sharma . Cost Efficient Query Optimization in Mobile Environment. International Journal of Computer Applications. 120, 22 ( June 2015), 30-38. DOI=10.5120/21394-4443

@article{ 10.5120/21394-4443,
author = { Reena Kasana, Saurabh Sharma },
title = { Cost Efficient Query Optimization in Mobile Environment },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 120 },
number = { 22 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-38 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume120/number22/21394-4443/ },
doi = { 10.5120/21394-4443 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:07:14.515143+05:30
%A Reena Kasana
%A Saurabh Sharma
%T Cost Efficient Query Optimization in Mobile Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 120
%N 22
%P 30-38
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Today, we live in the world of internet. With the advancement of technology, the amount of data access has increased too many folds. Internet access now is not only limited to computer devices but can now be easily accessed through mobile devices viz. Smartphones, tablets, PDA's. The internet is now available to every common man, and with its use he fires many queries on servers and uploads or downloads data from the internet. In fact, 90% of the world's data came in existence in the last three-four years, and that too because the internet is readily available to each and every common individual. Of these, much data is being uploaded and queried upon by mobile devices. As the number of devices for Internet access has increased, and so is the number of queries fired by the users on a particular server. The time taken by a query to process totally depends on the complexity involved in joining the tables distributed along the network and finally extracting the desired result out of it. Processing and optimization of various queries in mobile devices involve much join computation among data present at different sites that may be static or mobile which in turn requires much energy consumption. A mobile device has limited energy, so, it must be utilized efficiently. Much research work have been done till now, in the field of mobile computation and making efficient use of energy. However, as the mobile devices possess some asymmetric features, and because of that the old techniques used in distributed databases cannot be applied directly. This paper brings out some methods, to efficiently utilize mobile energy by employing per split semi-join using MapReduce Framework of Hadoop.

References
  1. D. Barbara, "Mobile Computing and Databases - A Survey," IEEE Transactions on Knowledge and Data Engineering, vol. 11, no. 1, pp. 108-117, January/February 1999.
  2. M. A. H. Hassan and M. Bamha, "Semi-join Computation on Distributed File System Using Map-Reducr-Merge Model," ACM, 22-26 March 2010.
  3. K. Shvachko, H. Kuang, S. Radia and R. Chansle, "The Hadoop Distributed File System," in Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), 2010.
  4. J. Venner, Pro Hadoop, Apress, June 22, 2009.
  5. T. White, Hadoop: The Definitive Guide, O'Reil.
  6. K. Karun A. and C. K. , "A review on hadoop — HDFS infrastructure extensions," in Information & Communication Technologies (ICT), 2013 IEEE Conference, pp. 132-137, April 11-12, 2013. .
  7. R. M. Arasanal and D. U. Rumani, "Improving MapReduce Performance through Complexity and Performance Based Data Placement in Heterogeneous Hadoop Clusters," 9th International Conference, ICDCIT 2013, vol. 7753, no. 1, pp. 115-125, February 5-8, 2013 .
  8. S. Blanas, J. M. Patel, V. Ercegovac, J. Rao, E. J. Shekita and Y. Tian, "A Comparison of Join Algorithms for Log Processing in Map-Reduce," in SIGMOD'10, Indianapolis, Indiana, USA. , June 6–11, 2010.
  9. "Applications of Mobile Computing," 2005. [Online]. Available: http://www. nokia. com/3g/ index. html.
  10. "Palm Pilots of 3com," 2005. [Online]. Available: http://www. palm. com.
  11. P. S. Yu, M. S. Chen and T. H. Yang, "On Coupling Multiple Systems with a Global Buffer," IEEE Trans. Knowledge and Data Engineering, vol. 8, no. 2, pp. 339-344, April 1996.
  12. P. S. Yu and M. S. Chen, "Interleaving A Join Sequence with Semijoins in Distributed Query Processing," IEEE Trans. Parallel and Distributed Systems, vol. 3, no. 5, pp. 611-622, September 1992.
  13. P. S. Yu and M. S. Chen, "Combining Join and Semi-Join Operations for Distributed Query Processing," IEEE Trans. Knowledge and Data Engineering, vol. 5, no. 3, pp. 534-542, June 1993.
  14. M. J. Franklin, B. T. Jonsson and D. Kossman, "Performance Tradeoffs for Client-Server Query," ACM SIGMOD International Conference on Management of Data, pp. 149-160, June 1996.
  15. C. Wang and M. S. Chen, "On the Complexity of Distributed Query Optimization," IEEE Transactions on Knowledge and Data Engineering, vol. 8, no. 4, pp. 650-662, August 1996.
  16. M. Koca, I. Ari, U. Kocak, O. Calikus and C. Sezgin, "Parallel and Pipelined processing of Large Scale Mobile communication data using Hadoop open-source framework," in 20th conference on Signal Processing and Communications Applications Conference (SIU), 2012, April 18-20, 2012.
  17. O. Choi, W. Jung, K. Kim and H. Yeh, "Mobile Cloud Computing Model for Data Processing," in 6th International Conference on New Trends in Information Science and Service Science and Data Mining (ISSDM), 2012, October 23-25, 2012.
  18. A. Datta, D. E. VanderMeer, A. Celik and V. Kumar, "Broadcast protocols to support efficient retrieval from databases by mobile users," ACM Transactions on Database Systems (TODS), vol. 24, no. 1, pp. 1-79, March 1999.
  19. R. Jain and N. Krishnakumar, "An asymmetric cost model for query processing in mobile computing environments," Wireless Information Networks, vol. 351, no. 1, pp. 363-377, 1996.
  20. R. Jain and N. Krishnakumar, "Asymmetric Costs and Dynamic Query Processing in Mobile Computing," 5th WINLAB workshop, April 1995.
  21. S. Ghemawat, H. Gobioff and S. T. Leung, "The Google File System," in SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems, The Sagamore, Bolton Landing (Lake George), October 19-22, 2003.
  22. F. Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D. A. Wallach, M. Burrows, T. Chandra, A. Fikes and R. E. Gruber, "Bigtable: A Distributed Storage System for Structured Data," OSDI '06: 7th USENIX Symposium on Operating Systems Design and Implementation, Berkeley, CA, USA, vol. 5, no. 1, pp. 205-218, 2006.
  23. "Apache Hadoop," [Online]. Available: http://hadoop. apache. org/core/.
  24. J. Xu and J. Liang, "Research on Distributed File System with Hadoop," Internatiaonal Journal of Communications in Computer and Information Science, vol. 345, no. 1, pp. 148-155, December 7-9, 2012.
  25. M. Bamha, "An Optimal Skew-insensitive Join and Multi-join Algorithm for Distributed Architectures," International Conference on Database and Expert System Applications, vol. 3588, no. 1, pp. 616-625, August 22-26, 2005.
  26. M. Bamha and G. Hains, "A Skew-Insensitive Algorithm for Join and Multi-join Operations on Shared Nothing Machines," International Journal of Database and Expert Systems Applications, vol. 1873, no. 1, pp. 644-653, 2000.
  27. M. Bamha and G. Hains, "Frequency-Adaptive Join for Shared Nothing Machines," Journal of Parallel and Distributed Computing Practices (PDCP), vol. 2, no. 3, pp. 333-345, September 1999.
  28. H. C. Yang, A. Dasdan, R. L. Hsiao and D. S. Parker, "Map-reduce-merge: simplified relational data processing on large clusters," Proceedings of the 2007 ACM SIGMOD international conference on Management of data, New York, USA, pp. 1029-1040, 2007.
  29. J. Dean and S. Ghemawat, "MapReduce: simplified data processing on large clusters," in Proceedings of the 6th conference on symposium on operating systems design and implementation, 2004.
  30. M. A. Hassan and M. Bamha, "Semi-join computation on distributed file systems using map-reduce-merge model," SAC '10 Proceedings of the 2010 ACM Symposium on Applied Computing, pp. 406-413, 2010.
  31. H. H. Le, S. Hikida and H. Yokota, "NameNode and DataNode Coupling for a Power-Proportional," 18th International Conference, DASFAA 2013, vol. 7826, no. 1, pp. 99-107, April 22-25, 2013.
  32. R. Pike, S. Dorward, R. Griesemer and S. Quin, "Interpreting the data: Parallel analysis with Sawzall," Scientific Programming - Dynamic Grids and Worldwide Computing, vol. 13, no. 4, pp. 277-298, October 2005.
  33. A. Pavlo, E. Paulson, A. Rasin, D. J. Abadi, D. J. DeWitt, S. Madden and M. Stoneb, "A comparision of approaches to Large-Scale Data Analysis," in SIGMOD'09, June 29-July 2, 2009.
  34. S. Blanas, J. M. Patel, V. Ercegovac, J. Rao, E. J. Shekita and Y. Tian, "A comparison of join algorithms for log processing in MaPreduce," SIGMOD '10 Proceedings of the 2010 ACM SIGMOD International Conference on Management of data, pp. 975-986, 2010.
  35. K. Shvachko, H. Kuang, S. Radia and R. Chansl, "The Hadoop Distributed File System," in Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST), 2010.
  36. S. Ganguly and R. Alonzo, "Query Optimization in Mobile Environments," 5th Workshop on Foundations of Models and Languages for Data and Objects, pp. 1-17, September 1993.
  37. M. H. Dunham and A. Helal, "Mobile Computing and Databases: anything new?," ACM SIGMOD Record, vol. 23, no. 4, pp. 5-9, December 1995.
  38. J. Jing, A. S. Helal and A. Elmagarmid, "Client-Server computing in mobile environments," ACM Computing Surveys (CSUR), vol. 31, no. 2, pp. 117-157, June 1999.
Index Terms

Computer Science
Information Sciences

Keywords

Per-Split Semi-Join MapReduce Hadoop Cost Optimization Distributed Databases

Powered by PhDFocusTM