INDEX SELECTION ENGINE FOR SPATIAL DATABASE SYSTEM MARUTO MASSERIE SARDADI UNIVERSITI TEKNOLOGI MALAYSIA

INDEX SELECTION ENGINE FOR SPATIAL DATABASE SYSTEM MARUTO MASSERIE SARDADI UNIVERSITI TEKNOLOGI MALAYSIA

INDEX SELECTION ENGINE FOR SPATIAL DATABASE SYSTEM MARUTO MASSERIE SARDADI A Thesis submitted in fulfilment of the requirement for the award for the degree of Master of Science (Computer Science) Faculty of Computer Science & Information Systems Universiti Teknologi Malaysia AUGUST 2010

iii To my God, Allah 'azza wa jalla and Dedicated to my mother and father whose love, encouragement and values will always guide and inspire me. Idawati Baskoro Sardadi and To my brother, Baruno Sardadi and my wife, Maulidya Maherany In the hope that they will be encouraged to strive for the best and thank you so much for being so patient and being there for me.

iv ACKNOWLEDGMENT In preparing this thesis, I was in contact with many people, researchers, academicians, and practitioners. They have contributed towards my understanding and thoughts. In particular, I wish to express my sincere appreciation to my main thesis supervisor, Assoc. Prof. Daut Daman, for encouragement, guidance, critics and friendship. I am also very thankful to my co-supervisors Dr. Mohd Shafry Mohd Rahim and En. Zahabidin Jupri for their guidance, advices and motivation. And another lecture was also gave some supports in my study, En. Daud Kasmuni. Without their continued support and interest, this thesis would not have been the same as presented here. I am also indebted to Universiti Teknologi Malaysia (UTM) for funding my Master study. Librarians at UTM also deserve special thanks for their assistance in supplying the relevant literatures. My fellow from Indonesian Student Association (PPI) should also be recognized for their support. My sincere appreciation also extends to all my colleagues and others who have provided assistance at various occasions. Their views and tips are useful indeed. Unfortunately, it is not possible to list all of them in this limited space. I am grateful to all my family members.

v ABSTRACT The latest mobile Geographical Information System (GIS) technology is useful to manage spatial components of various daily business projects in corporate databases. It is important to apply proper geographical analysis efficiently in a wireless application. However, one of the problems of wireless internet is system bottlenecks that can slow down data processing in Mobile GIS. Spatial data indexing is one of the methods to speed up spatial queries. The existing spatial data indexing can only change the index used. However, an indexing method is only better for some ranges of data and conditions. The objective of this research is to speed up access to spatial database system by using spatial index selection engine. This research introduces an index selection engine for spatial database system for every condition and range of data, on top of the basic index structure. The index selection engine, which is called QuadRtree Selection engine, uses a rule-based Knowledge Base Expert System (KBES) to select between R-tree and Quadtree spatial data indices. These spatial data indexing methods are the best spatial data indexing methods among many other existing spatial index methods for low-dimensional spatial data which have different advantages and disadvantages based on the condition of spatial data. The result of using the proposed method can save time up to 42.5% compared to not using this method.

vi ABSTRAK Teknologi Sistem Maklumat Geografi (GIS) mudah alih terkini berguna untuk mengurus komponen ruang dalam pelbagai urusan harian projek perniagaan pada pangkalan data koprat. Teknologi ini penting untuk penggunaan analisa geografi secara efisen dalam aplikasi tanpa wayar. Namun, teknologi tanpa wayar ini boleh melambatkan proses pemindahan data akibat daripada kesesakan laluan sistem di dalam teknologi GIS mudah alih. Mengindeks data ruang merupakan salah satu kaedah untuk mempercepatkan pertanyaan berasaskan ruang. Kaedah peningkatan mengindeks data ruang yang sedia ada hanya boleh mengubah indeks yang digunakan. Namun, kaedah mengindeks hanya lebih baik untuk beberapa julat data dan keadaan. Objektif penyelidikan ini adalah untuk mempercepatkan capaian pada sistem pangkalan data ruang dengan menggunakan mesin pemilihan indeks ruang. Penyelidikan ini memperkenalkan mesin pemilihan indeks untuk sistem pangkalan data ruang dalam setiap keadaan dan pelbagai julat data, ke atas struktur asas indeks. Mesin pemilihan indeks ini, yang disebut mesin pemilihan QuadRtree, menggunakan Pangkalan Pengetahuan Sistem Pakar berasaskan peraturan untuk memilih antara indeks data ruang R-tree dan Quadtree. Kaedah mengindeks data ruang ini adalah kaedah mengindeks data ruang yang terbaik di antara banyak kaedah pengindeks data ruang yang sedia ada untuk data yang berdimensi rendah di mana mempunyai perbezaan kelebihan dan kekurangan berdasarkan keadaan data ruang. Keputusan menggunakan kaedah yang dicadangkan boleh menjimatkan masa sehingga 42.5% dibandingkan dengan tidak menggunakan kaedah ini.