A multi-copy join optimization of information integration systems based on a genetic algorithm - Details

Author：

Fang, Liying (Fang, Liying.) | Wang, Pu (Wang, Pu.) | Yan, Jianzhuo (Yan, Jianzhuo.)

Indexed by：

EI Scopus

Abstract：

In　view　of　inevitable　redundancies　in　local　data　sources　in　heterogeneous　information　integration　systems,　a　multi-copy　join　optimization　method　(MuCoJo　for　short)　based　on　a　genetic　algorithm　is　proposed.　MuCoJo　can　choose　appropriate　redundant　copies　of　the　tables　to　participate　a　joint　query　and　optimizes　the　join　order　of　it.　By　using　the　redundant　copies,　MuCoJo　enlarges　the　search　space　so　that　the　concurrent　executions　of　different　local　sources　can　be　best　used　.Meanwhile,　MuCoJo　could　take　advantage　of　redundancies　features　in　such　systems　and　get　faster　joint　query　response　time.　Experimental　results　show　the　computational　efficiency　of　the　MuCoJo　and　its　necessity　in　information　integration　system.　Moreover,　during　the　population　initialization,　controlling　invalid　solutions　can　reduce　the　search　space　effectively　at　the　cost　of　initialization　time　consuming.　©　2008　IEEE.

Keyword：

Redundancy Genetic algorithms Computation theory Computational efficiency Information retrieval Peer to peer networks Integration

Author Community：

[ 1 ] [Fang, Liying]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
[ 2 ] [Wang, Pu]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China
[ 3 ] [Yan, Jianzhuo]College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100022, China