Cuckoo Search-Based View Selection

A data warehouse is a central store of all entities, concepts, metadata and historical information created for doing data validation, complex mining, analysis and prediction in many organizations. A data warehouse is designed primarily as a tool for answering analytical queries, which are intricate and exploratory and have higher response times when answered using a data warehouse. Many real enterprise information integration systems compute and maintain materialized views or cache results. Unlike virtual views, materialized views store data. Since all views cannot be materialized due to storage space constraints, an appropriate subset of views needs to be selected for materialization. The selection of such a subset is an NP-complete problem. Swarm intelligence algorithms have been extensively used to resolve such problems. In this paper, the cuckoo search (CS) algorithm has been adapted and discretized to solve the view selection problem. Based on this, a CS-based view selection algorithm (CSVSA) has been proposed. Also, experiments were performed to ascertain appropriate parameter values for which CSVSA is able to select reasonably good quality Top-K.

[1]  T. V. Vijay Kumar,et al.  Materialized View Selection using Marriage in Honey Bees Optimization , 2015, Int. J. Nat. Comput. Res..

[2]  Rada Chirkova,et al.  A formal perspective on the view selection problem , 2002, The VLDB Journal.

[3]  T. V. Vijay Kumar,et al.  A Query Answering Greedy Algorithm for Selecting Materialized Views , 2010, ICCCI.

[4]  T. V. Vijay Kumar,et al.  Materialized View Selection Using Memetic Algorithm , 2013, MIKE.

[5]  Efraim Turban,et al.  Decision Support Systems and Intelligent Systems (7th Edition) , 2004 .

[6]  Ziqiang Wang,et al.  An Efficient Materialized Views Selection Algorithm Based on PSO , 2009, 2009 International Workshop on Intelligent Systems and Applications.

[7]  Inderpal Singh Mumick,et al.  Selection of views to materialize in a data warehouse , 1997, IEEE Transactions on Knowledge and Data Engineering.

[8]  T. V. Vijay Kumar,et al.  A Reduced Lattice Greedy Algorithm for Selecting Materialized Views , 2009, ICISTM.

[9]  Vicki L. Sauter,et al.  Decision Support Systems for Business Intelligence: Sauter/Decision , 2011 .

[10]  T. V. Vijay Kumar,et al.  Greedy Views Selection Using Size and Query Frequency , 2011 .

[11]  Surajit Chaudhuri,et al.  An overview of data warehousing and OLAP technology , 1997, SGMD.

[12]  Jeffrey F. Naughton,et al.  Materialized View Selection for Multidimensional Datasets , 1998, VLDB.

[13]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[14]  T. V. Vijay Kumar,et al.  An Architectural Framework for Constructing Materialized Views in a Data Warehouse , 2013 .

[15]  Bela Stantic,et al.  Simulated Annealing for Materialized View Selection in Data Warehousing Environment , 2006, Databases and Applications.

[16]  T. V. Vijay Kumar,et al.  Answering query-based selection of materialised views , 2013, Int. J. Inf. Decis. Sci..

[17]  T. V. Vijay Kumar,et al.  Selection of Views for Materialization Using Size and Query Frequency , 2011 .

[18]  Neeraj Jain,et al.  Mining information for constructing materialised views , 2010, Int. J. Inf. Commun. Technol..

[19]  T. V. Vijay Kumar,et al.  Query answering-based view selection , 2015, Int. J. Bus. Inf. Syst..

[20]  Jeffrey F. Naughton,et al.  Materialized View Selection for Multi-Cube Data Models , 2000, EDBT.

[21]  Xin Yao,et al.  Evolving materialized views in data warehouse , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[22]  T. V. Vijay Kumar,et al.  Materialised views selection using size and query frequency , 2011 .

[23]  Minsoo Lee,et al.  Speeding Up Materialized View Selection in Data Warehouses Using a Randomized Algorithm , 2001, Int. J. Cooperative Inf. Syst..

[24]  Jian Yang,et al.  Algorithms for Materialized View Design in Data Warehousing Environment , 1997, VLDB.

[25]  Qing Li,et al.  Design and selection of materialized views in a data warehousing environment: a case study , 1999, DOLAP '99.

[26]  T. V. Vijay Kumar,et al.  Materialized View Selection using Improvement based Bee Colony Optimization , 2015, Int. J. Softw. Sci. Comput. Intell..

[27]  Santosh Kumar,et al.  Materialised view selection using differential evolution , 2014 .

[28]  T. V. Vijay Kumar,et al.  A View Recommendation Greedy Algorithm for Materialized Views Selection , 2011, ICISTM.

[29]  T. V. Vijay Kumar,et al.  Materialized View Selection Using Iterative Improvement , 2012, ACITY.

[30]  Nigel Davies.  Cuckoo adaptations: trickery and tuning , 2011 .

[31]  T. V. Vijay Kumar,et al.  Materialised view selection using randomised algorithms , 2015, Int. J. Bus. Inf. Syst..

[32]  T. V. Vijay Kumar,et al.  Materialized View Selection Using Simulated Annealing , 2012, BDA.

[33]  T. V. Vijay Kumar,et al.  Materialised view construction in data warehouse for decision making , 2012, Int. J. Bus. Inf. Syst..

[34]  T. V. Vijay Kumar,et al.  Materialized View Selection Using Genetic Algorithm , 2012, IC3.

[35]  Jeffrey D. Ullman,et al.  Index selection for OLAP , 1997, Proceedings 13th International Conference on Data Engineering.

[36]  Michael Lawrence,et al.  Multiobjective genetic algorithms for materialized view selection in OLAP data warehouses , 2006, GECCO '06.

[37]  Vicki L. Sauter,et al.  Decision Support Systems for Business Intelligence , 2011 .

[38]  Jeffrey D. Ullman,et al.  Implementing data cubes efficiently , 1996, SIGMOD '96.

[39]  Toby J. Teorey,et al.  Achieving scalability in OLAP materialized view selection , 2002, DOLAP '02.

[40]  Xin Yao,et al.  Materialized view selection as constrained evolutionary optimization , 2003, IEEE Trans. Syst. Man Cybern. Part C.

[41]  T. V. Vijay Kumar,et al.  Materialised view selection using BCO , 2016, Int. J. Bus. Inf. Syst..

[42]  T. V. Vijay Kumar,et al.  Materialized Views Selection for Answering Queries , 2010, ICDEM.

[43]  Cheng-Yan Kao,et al.  Materialized view selection using genetic algorithms in a data warehouse system , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[44]  T. V. Vijay Kumar,et al.  Proposing Candidate Views for Materialization , 2010, ICISTM.