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JCR Impact Factor: 0.595
JCR 5-Year IF: 0.661
Issues per year: 4
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Avg review time: 108 days


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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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LATEST NEWS

2017-Jun-14
Thomson Reuters published the Journal Citations Report for 2016. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.595, and the JCR 5-Year Impact Factor is 0.661.

2017-Apr-04
We have the confirmation Advances in Electrical and Computer Engineering will be included in the EBSCO database.

2017-Feb-16
With new technologies, such as mobile communications, internet of things, and wide applications of social media, organizations generate a huge volume of data, much faster than several years ago. Big data, characterized by high volume, diversity and velocity, increasingly drives decision making and is changing the landscape of business intelligence, from governments to private organizations, from communities to individuals. Big data analytics that discover insights from evidences has a high demand for computing efficiency, knowledge discovery, problem solving, and event prediction. We dedicate a special section of Issue 4/2017 to Big Data. Prospective authors are asked to make the submissions for this section no later than the 31st of May 2017, placing "BigData - " before the paper title in OpenConf.

2017-Jan-30
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2016-Dec-17
IoT is a new emerging technology domain which will be used to connect all objects through the Internet for remote sensing and control. IoT uses a combination of WSN (Wireless Sensor Network), M2M (Machine to Machine), robotics, wireless networking, Internet technologies, and Smart Devices. We dedicate a special section of Issue 2/2017 to IoT. Prospective authors are asked to make the submissions for this section no later than the 31st of March 2017, placing "IoT - " before the paper title in OpenConf.

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  2/2010 - 14

Cache Pattern with Multi-Queries

TUDOR, N. L. See more information about TUDOR, N. L. on SCOPUS See more information about TUDOR, N. L. on IEEExplore See more information about TUDOR, N. L. on Web of Science
 
Click to see author's profile on See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (635 KB) | Citation | Downloads: 758 | Views: 2,692

Author keywords
equivalence class of queries from the cache, multiple queries optimization, multi-query caching, set of cache patterns, the heuristic of pair queries

References keywords
query(8), optimization(8), database(8), data(6), sudarshan(5), sigmod(5), naughton(4), databases(4), caching(4)
No common words between the references section and the paper title.

About this article
Date of Publication: 2010-05-31
Volume 10, Issue 2, Year 2010, On page(s): 82 - 86
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2010.02014
Web of Science Accession Number: 000280312600014
SCOPUS ID: 77954652006

Abstract
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This article proposes a cache pattern with multi-queries and describes the multi-query optimization with scheduling, caching and pipelining. A set of cache patterns is derived from a set of class of multi-queries that are loaded into the cache. Each cache pattern represents a unique equivalence class in the set of patterns. The multi-query optimization with scheduling, caching and pipelining provides efficient heuristics, for a good queries ordering using a single invocation on the entire batch of queries. Multi-query optimization chooses the results of sub-expression that should be admitted to or discarded from cache, when it executes queries. We introduce the heuristic of pair queries and define the equivalence class of multi-queries from cache pattern. We show that the union of all equivalence classes of queries from the cache patterns is the set of cache patterns.


References | Cited By  «-- Click to see who has cited this paper

[1] A.A. Diwan, S. Sudarshan, D. Thomas, "Scheduling and Caching in Multi-Query Optimization", International Conference on Management of Data COMAD, Delhi, India, 2006.

[2] P. Roy, "MultiQuery Optimization and Applications", PhD thesis, IIT Bombay, 2000.

[3] S. N. Subramanian, S. Venkataraman, "Cost based optimization of decision support queries using transient views", In ACM SIGMOD Intl. Conf. Management of Data, Seattle, WA, 1998.
[CrossRef]


[4] H. Mistry, P. Roy, S. Sudarshan, K. Ramamritham, "Materialized view selection and maintenance using multi-query optimization", In ACM SIGMOD Intl. Conf. Management of Data, 2001.
[CrossRef]


[5] J. Shanmugasundaram, G. He, K. Tufte, C. Zhang, D. De-Witt, J. Naughton, "Relational databases for querying XML documents: Limitations and opportunities", In Intl. Conf. Very Large Databases, 1999.

[6] J. Chen, D. J. DeWitt, J. F. Naughton, "Design and evaluation of alternative selection placement strategies in optimizing continuous queries", IEEE Intl. Conf. Data Engineering, 2002.
[CrossRef] [Web of Science Times Cited 17]


[7] Sellis, T.K.: Multiple-Query Optimization, ACM Trans. Database Syst. 13(1), pp. 23-52, 1988.
[CrossRef] [Web of Science Times Cited 195] [SCOPUS Times Cited 382]


[8] Roy, P., Seshadri, S., Sudarshan, S., Bhobe, S., "Efficient and Extensible Algorithms for Multi Query Optimization", SIGMOD, 2000.
[CrossRef] [SCOPUS Times Cited 227]


[9] X. Wang, T. Malik, R. Burns, S. Papadomanolakis, A. Ailamaki, "A Workload-Driven Unit of Cache Replacement for Mid-Tier Database Caching", SIGMOD, 2002.

[10] A. Gupta, S. Sudarshan, S. Viswanathan, "Query scheduling in multiquery optimization", In IDEAS, pp. 11-19, 2001.

[11] N. N. Dalvi, S. K. Sanghai, P. Roy, and S. Sudarshan, "Pipelining in multiquery optimization", ACM Symp. Principles of Database Systems, 2001.
[CrossRef]


[12] K.-L. Tan, H. Lu, "Workload scheduling for multiple query processing", Information Processing Letters, 555, pp. 251-257, 1995.
[CrossRef] [Web of Science Times Cited 8] [SCOPUS Times Cited 13]


[13] Q.Luo, J. F. Naughton, R. Krishnamurthy, P. Cao, Y. Li, "Active Query Caching for Database Web Servers", ACM SIGMOD Workshop on the Web and Databases, WebDB, 2000.
[CrossRef]


[14] Q. Luo, J. F Naughton, "Form-Based Proxy Caching for Database-Backed Web Sites", VLDB Conference, Rome 2001.

[15] Sophie Cluet, Olga Kapitskaia, Divesh Srivastava, "Using LDAP Directory Caches", Proc. ACM Principles of Database Systems,1999.

[16] Olga Kapitskaia, Raymond T Ng, Divesh Srivastava, "Evolution and revolutions in LDAP directory caches", Proceedings of the International Conference on Extending Database Technology (EDBT), pp. 202-216, 2000.
[CrossRef]


[17] Papadomanolakis, S., Ailamaki, A., "AutoPart: Automating Schema Design for Large Scientific Databases Using Data Partitioning", SSDBM, 2004.

[18] Nastasescu C., Nita C., Vraciu C., Bazele algebrei, vol I, Editura Academiei Romaniei, Bucuresti, 1986.

[19] G. Graefe, W. J. McKenna, "Extensibility and Search Efficiency in the Volcano Optimizer Generator", In IEEE Intl. Conf. Data Engineering, 1993.
[CrossRef]


[20] J. Flum, M. Frick, M. Grohe, "Query Evaluation via Tree-Decompositions", Proc. of the 8th International Conference on Database Theory (ICDT'01), volume 1973 of Lecture Notes in Computer Science, pp. 22-38, UK, 2001, Springer.
[CrossRef]


References Weight

Web of Science® Citations for all references: 220 TCR
SCOPUS® Citations for all references: 622 TCR

Web of Science® Average Citations per reference: 11 ACR
SCOPUS® Average Citations per reference: 31 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2017-10-14 07:29 in 78 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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