The Community for Technology Leaders
RSS Icon
Subscribe
Issue No.01 - January-March (2011 vol.18)
pp: 64-77
K. Selcuk Candan , Arizona State University
Jong Kim , Arizona State University
Parth Nagarkar , Arizona State University
Mithila Nagendra , Arizona State University
Renwei Yu , Arizona State University
ABSTRACT
<p>RanKloud is an efficient, scalable, utility-aware, parallel-processing system for analysis of large media data sets. The Web extra includes a Power Point-based presentation of the RanKloud framework, followed by an example showing the use of RanKloud within a top-K query processing scenario. View the same Web extra online at http://www.youtube.com/watch?v=cD-VK0SlvvM.</p>
INDEX TERMS
Large-scale multimedia processing, cluster architectures, ranked query processing, top-k, nearest neighbor, MapReduce, data and work partitioning, sampling.
CITATION
K. Selcuk Candan, Jong Kim, Parth Nagarkar, Mithila Nagendra, Renwei Yu, "RanKloud: Scalable Multimedia Data Processing in Server Clusters", IEEE MultiMedia, vol.18, no. 1, pp. 64-77, January-March 2011, doi:10.1109/MMUL.2010.70
REFERENCES
1. C. Bohm and F. Krebs, "High Performance Data Mining Using the Nearest Neighbor Join," Proc. IEEE Int'l Conf. Data Mining, IEEE CS Press, 2002, pp. 43-50.
2. S. Poullot, M. Crucianu, and O. Buisson, "Scalable Mining of Large Video Databases Using Copy Detection," Proc. Int'l Multimedia Conf., ACM Press, 2008, pp. 61-70.
3. X. Yang, Q. Zhu, and K.T. Cheng, "Near- Duplicate Detection for Images and Videos," Proc. 1st ACM Workshop Large-Scale Multimedia Retrieval and Mining, ACM Press, 2009, pp. 73-80.
4. J.W. Kim, K.S. Candan, and J. Tatemura, "Efficient Overlap and Content Reuse Detection in Blogs and Online News Articles," Proc. WWW Conf., ACM Press, 2009, pp. 81-90.
5. J. Dean and S. Ghemawat, "MapReduce: Simplified Data Processing on Large Clusters," Proc. Symp. Operating Systems Design & Implementation, Usenix Assoc., 2004.
6. C. Olston et al., "Pig Latin: A Not-So-Foreign Language for Data Processing," Proc. Sigmod Conf., ACM Press, 2008, pp. 1099-1110.
7. W.-Y Chen et al., "Collaborative Filtering for Orkut Communities: Discovery of User Latent Behavior," Proc. WWW Conf., ACM Press, 2009.
8. W.-Y Chen et al., "Large-Scale Spectral Clustering with MapReduce and MPI," Scaling Up Machine Learning, R. Bekkerman, M. Bilenko, J. Langford eds., Cambridge University Press, 2010.
9. R. Vernica, M. Carey, and C. Li, "Efficient Parallel Set-Similarity Joins Using MapReduce," Proc. Sigmod Conf., ACM Press, 2010.
10. H. Li et al., "PFP: Parallel FP-Growth Algorithm for Query Recommendation," Proc. ACM Conf. Recommender Systems, ACM Press, 2008.
11. R. Yu et al., Workload-Balanced Processing of Top- K Join Queries on Cluster Architectures, tech. report ASUCIDSE-CSE-2010-001, Arizona State Univ., 2010.
12. R. Fagin, "Fuzzy Queries in Multimedia Database Systems," Proc. Symp. Principles of Database Systems, ACM Press, 1998, pp. 216-226.
13. R. Fagin, A. Lotem, and M. Naor, "Optimal Aggregation Algorithms for Middleware, J. Computer and System Sciences, vol. 66, no. 4, 2003, pp. 614-656.
14. M. Nagendra, "Efficient Processing of Join-Based Skyline Queries on Batch-Oriented Cluster Architectures," master's thesis, School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., 2010.
101 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool