The Optimization of Running Queries in Relational Databases Using ANT-Colony Algorithm

TL;DR

This paper proposes a heuristic ant colony algorithm to optimize query execution in relational databases, specifically targeting join operations to reduce runtime and improve efficiency.

Contribution

It introduces a novel application of the ant colony algorithm for query optimization, demonstrating improved performance over existing methods.

Findings

The algorithm reduces query execution time significantly.

Experimental results show higher efficiency compared to similar algorithms.

The approach effectively handles complex join permutations.

Abstract

The issue of optimizing queries is a cost-sensitive process and with respect to the number of associated tables in a query, its number of permutations grows exponentially. On one hand, in comparison with other operators in relational database, join operator is the most difficult and complicated one in terms of optimization for reducing its runtime. Accordingly, various algorithms have so far been proposed to solve this problem. On the other hand, the success of any database management system (DBMS) means exploiting the query model. In the current paper, the heuristic ant algorithm has been proposed to solve this problem and improve the runtime of join operation. Experiments and observed results reveal the efficiency of this algorithm compared to its similar algorithms.