Distributed query plan generation using multi-objective ant colony optimisation

In distributed relational databases, relations are fragmented and replicated at multiple disparate sites. As a result, for a distributed relational query, the number of possible query plans increases exponentially with an increase in the number of sites containing these relations. This leads to a large search space from which effective and efficient query plans are to be computed. This problem has already been addressed as a single objective optimisation problem using ant colony optimisation. In this paper, this problem is addressed as a bi-objective optimisation problem and solved using multi-objective ant colony optimisation MOACO. Accordingly, a MOACO-based distributed query plan generation DQPG algorithm is proposed herein that generates Top-K query plans for a distributed query. Experimental comparisons of the proposed MOACO-based DQPG algorithm with the existing ACO-based DQPG algorithm show that for higher numbers of relations, the former is able to generate, comparatively, cost-effective Top-K query plans.

[1]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[2]  Francisco Herrera,et al.  A taxonomy and an empirical analysis of multiple objective ant colony optimization algorithms for the bi-criteria TSP , 2007, Eur. J. Oper. Res..

[3]  Christian Blum,et al.  Ant colony optimization: Introduction and recent trends , 2005 .

[4]  Eugene Wong,et al.  Query optimization by simulated annealing , 1987, SIGMOD '87.

[5]  Kalyanmoy Deb,et al.  Multi-objective optimization using evolutionary algorithms , 2001, Wiley-Interscience series in systems and optimization.

[6]  Matthias Jarke,et al.  Query Optimization in Database Systems , 1984, CSUR.

[7]  N. Parimala,et al.  Querying Multidatabase Systems Using SIQL , 2002, FQAS.

[8]  Yannis E. Ioannidis,et al.  Randomized algorithms for optimizing large join queries , 1990, SIGMOD '90.

[9]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[10]  Charles J. Petrie,et al.  Using Pareto optimality to coordinate distributed agents , 1995, Artif. Intell. Eng. Des. Anal. Manuf..

[11]  Stefano Ceri,et al.  Distributed Databases: Principles and Systems , 1984 .

[12]  Yannis E. Ioannidis,et al.  Left-deep vs. bushy trees: an analysis of strategy spaces and its implications for query optimization , 1991, SIGMOD '91.

[13]  Kalyanmoy Deb,et al.  On finding multiple Pareto-optimal solutions using classical and evolutionary generating methods , 2007, Eur. J. Oper. Res..

[14]  Patrick Valduriez,et al.  Principles of Distributed Database Systems , 1990 .

[15]  Patrick Valduriez,et al.  Distributed database systems: where are we now? , 1991, Computer.

[16]  Martin J. Oates,et al.  PESA-II: region-based selection in evolutionary multiobjective optimization , 2001 .

[17]  Christine Solnon,et al.  Ant Colony Optimization for Multi-Objective Optimization Problems , 2007 .

[18]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[19]  Carlos A. Coello Coello,et al.  A Comprehensive Survey of Evolutionary-Based Multiobjective Optimization Techniques , 1999, Knowledge and Information Systems.

[20]  Clement T. Yu,et al.  Distributed query processing , 1984, CSUR.

[21]  Arun N. Swami,et al.  Optimization of large join queries , 1988, SIGMOD '88.

[22]  Kalyanmoy Deb,et al.  Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms , 1994, Evolutionary Computation.

[23]  T. Stützle,et al.  A Review on the Ant Colony Optimization Metaheuristic: Basis, Models and New Trends , 2002 .

[24]  David E. Goldberg,et al.  A niched Pareto genetic algorithm for multiobjective optimization , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[25]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[26]  Donald Kossmann,et al.  The state of the art in distributed query processing , 2000, CSUR.

[27]  Thomas Stützle,et al.  Ant Colony Optimization , 2009, EMO.

[28]  K. Deb.  Solving goal programming problems using multi-objective genetic algorithms , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[29]  Ioana Manolescu,et al.  Query optimization in the presence of limited access patterns , 1999, SIGMOD '99.

[30]  Marco Dorigo,et al.  Ant colony optimization theory: A survey , 2005, Theor. Comput. Sci..

[31]  Patrick Valduriez,et al.  Distributed and parallel database systems , 1996, CSUR.

[32]  Matthias Ehrgott,et al.  Multicriteria Optimization , 2005 .

[33]  Michael Stonebraker,et al.  Distributed query processing in a relational data base system , 1978, SIGMOD Conference.

[34]  Kaisa Miettinen,et al.  Nonlinear multiobjective optimization , 1998, International series in operations research and management science.

[35]  Thomas Stützle,et al.  Automatic Configuration of Multi-Objective ACO Algorithms , 2010, ANTS Conference.

[36]  Rahul Singh,et al.  Distributed Query Plan Generation using Ant Colony Optimization , 2015, Int. J. Appl. Metaheuristic Comput..