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A Dual Framework and Algorithms for Targeted Online Data Delivery
January 2011 (vol. 23 no. 1)
pp. 5-21
ASCII Text
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Haggai Roitman, Avigdor Gal, Louiqa Raschid, "A Dual Framework and Algorithms for Targeted Online Data Delivery," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 1, pp. 5-21, January, 2011.
 
 
BibTex
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@article{ 10.1109/TKDE.2010.15,
author = {Haggai Roitman and Avigdor Gal and Louiqa Raschid},
title = {A Dual Framework and Algorithms for Targeted Online Data Delivery},
journal ={IEEE Transactions on Knowledge and Data Engineering},
volume = {23},
number = {1},
issn = {1041-4347},
year = {2011},
pages = {5-21},
doi = {http://doi.ieeecomputersociety.org/10.1109/TKDE.2010.15},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - JOUR
JO - IEEE Transactions on Knowledge and Data Engineering
TI - A Dual Framework and Algorithms for Targeted Online Data Delivery
IS - 1
SN - 1041-4347
SP5
EP21
EPD - 5-21
A1 - Haggai Roitman,
A1 - Avigdor Gal,
A1 - Louiqa Raschid,
PY - 2011
KW - Distributed databases
KW - online information services
KW - client/server multitier systems
KW - online data delivery.
VL - 23
JA - IEEE Transactions on Knowledge and Data Engineering
ER -
 
Haggai Roitman, IBM, Haifa
Avigdor Gal, Technion - Israel Institute of Technology, Haifa
Louiqa Raschid, University of Maryland, College Park
A variety of emerging online data delivery applications challenge existing techniques for data delivery to human users, applications, or middleware that are accessing data from multiple autonomous servers. In this paper, we develop a framework for formalizing and comparing pull-based solutions and present dual optimization approaches. The first approach, most commonly used nowadays, maximizes user utility under the strict setting of meeting a priori constraints on the usage of system resources. We present an alternative and more flexible approach that maximizes user utility by satisfying all users. It does this while minimizing the usage of system resources. We discuss the benefits of this latter approach and develop an adaptive monitoring solution Satisfy User Profiles (SUPs). Through formal analysis, we identify sufficient optimality conditions for SUP. Using real (RSS feeds) and synthetic traces, we empirically analyze the behavior of SUP under varying conditions. Our experiments show that we can achieve a high degree of satisfaction of user utility when the estimations of SUP closely estimate the real event stream, and has the potential to save a significant amount of system resources. We further show that SUP can exploit feedback to improve user utility with only a moderate increase in resource utilization.

[1] A. Adi and O. Etzion, "Amit—The Situation Manager," Int'l J. Very Large Data Bases, vol. 13, no. 2, pp. 177-203, May 2004.
[2] L. Bright, A. Gal, and L. Raschid, "Adaptive Pull-Based Policies for Wide Area Data Delivery," ACM Trans. Database Systems, vol. 31, no. 2, pp. 631-671, 2006.
[3] L. Bright and L. Raschid, "Using Latency-Recency Profiles for Data Delivery on the Web," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 550-561, Aug. 2002.
[4] D. Carney, S. Lee, and S. Zdonik, "Scalable Application-Aware Data Freshening," Proc. IEEE CS Int'l Conf. Data Eng., pp. 481-492, Mar. 2003.
[5] L.S. Chandran, L. Ibarra, F. Ruskey, and J. Sawada, "Generating and Characterizing the Perfect Elimination Orderings of a Chordal Graph," Theoretical Computer Science, vol. 307, no. 2, pp. 303-317, 2003.
[6] M. Cherniack, E. Galvez, M. Franklin, and S. Zdonik, "Profile-Driven Cache Management," Proc. IEEE CS Int'l Conf. Data Eng., pp. 645-656, Mar. 2003.
[7] J. Cho and H. Garcia-Molina, "Synchronizing a Database to Improve Freshness," Proc. ACM SIGMOD, pp. 117-128, May 2000.
[8] J. Cho and A. Ntoulas, "Effective Change Detection Using Sampling," Proc. Int'l Conf. Very Large Data Bases (VLDB), 2002.
[9] "CNN Top Stories RSS Feed," http://rss.cnn.com/services/rsscnn_topstories.rss , 2010.
[10] E. Cohen and H. Kaplan, "Refreshment Policies for Web Content Caches," Proc. IEEE INFOCOM, pp. 1398-1406, Apr. 2001.
[11] U. Dayal et al., "The HiPAC Project: Combining Active Databases and Timing Constraints," SIGMOD Record, vol. 17, no. 1, pp. 51-70, Mar. 1988.
[12] P. Deolasee, A. Katkar, P. Panchbudhe, K. Ramamritham, and P. Shenoy, "Adaptive Push-Pull: Disseminating Dynamic Web Data," Proc. Int'l World Wide Web Conf. (WWW), pp. 265-274, May 2001.
[13] J. Eckstein, A. Gal, and S. Reiner, "Optimal Information Monitoring under a Politeness Constraint," Technical Report RRR 16-2005, RUTCOR, Rutgers Univ., May 2005.
[14] A. Gal and J. Eckstein, "Managing Periodically Updated Data in Relational Databases: A Stochastic Modeling Approach," J. ACM, vol. 48, no. 6, pp. 1141-1183, 2001.
[15] J. Gwertzman and M. Seltzer, "World Wide Web Cache Consistency," Proc. USENIX Ann. Technical Conf., pp. 141-152, Jan. 1996.
[16] "BlackBerry Wireless Handhelds," http:/www.blackberry.com, 2010.
[17] Z. Jiang and L. Kleinrock, "Prefetching Links on the WWW," Proc. IEEE Int'l Conf. Comm., 1997.
[18] G. Kappel, S. Rausch-Schott, and Retschitzegger, "Beyond Coupling Modes: Implementing Active Concepts on Top of a Commercial OODBMS," Object-Oriented Methodologies and Systems, S. Urban and E. Bertino, eds., pp. 189-204. Springer-Verlag, 1994.
[19] J.-J. Lee, K.-Y. Whang, B.S. Lee, and J.-W. Chang, "An Update-Risk Based Approach to TTL Estimation in Web Caching," Proc. Conf. Web Information Systems Eng. (WISE), pp. 21-29, Dec. 2002.
[20] C. Liu and P. Cao, "Maintaining Strong Cache Consistency on the World Wide Web," Proc. Int'l Conf. Distributed Computing Systems (ICDCS), 1997.
[21] H. Liu, V. Ramasubramanian, and E.G. Sirer, "Client and Feed Characteristics of rss, a Publish-Subscribe System for Web Micronews," Proc. Internet Measurement Conf. (IMC), Oct. 2005.
[22] C. Olston and J. Widom, "Best-Effort Cache Synchronization with Source Cooperation," Proc. ACM SIGMOD, pp. 73-84, 2002.
[23] V. Padmanabhan and J. Mogul, "Using Predictive Prefetching to Improve World Wide Web Latency," ACM SIGCOMM Computer Comm. Rev., vol. 26, no. 3, pp. 22-36, July 1996.
[24] S. Pandey, K. Dhamdhere, and C. Olston, "WIC: A General-Purpose Algorithm for Monitoring Web Information Sources," Proc. Int'l Conf. Very Large Data Bases (VLDB), pp. 360-371, Sept. 2004.
[25] "Promo Language Specification," http://ie.technion.ac.il/ ~avigalProMoLang.pdf , 2010.
[26] H. Roitman, A. Gal, and L. Raschid, "Capturing Approximated Data Delivery Tradeoffs," Proc. IEEE CS Int'l Conf. Data Eng., 2008.
[27] "RSS," http:/www.rss-specifications.com, 2010.
[28] J.L. Wolf, M.S. Squillante, P.S. Yu, J. Sethuraman, and L. Ozsen, "Optimal Crawling Strategies for Web Search Engines," Proc. Int'l World Wide Web Conf. (WWW), pp. 136-147, 2002.
[29] E. Yashchin, "Change-Point Models in Industrial Applications," Nonlinear Analysis, vol. 30, pp. 3997-4006, 1997.
[30] J. Yin, L. Alvisi, M. Dahlin, and A. Iyengar, "Engineering Server-Driven Consistency for Large Scale Dynamic Web Services," Proc. Int'l World Wide Web Conf. (WWW), pp. 45-57, May 2001.

Index Terms:
Distributed databases, online information services, client/server multitier systems, online data delivery.
Citation:
Haggai Roitman, Avigdor Gal, Louiqa Raschid, "A Dual Framework and Algorithms for Targeted Online Data Delivery," IEEE Transactions on Knowledge and Data Engineering, vol. 23, no. 1, pp. 5-21, Jan. 2011, doi:10.1109/TKDE.2010.15
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