ENHANCING CLUSTERING NETWORK PLANNING ALGORITHM IN THE PRESENCE OF OBSTACLES

Lamia Fattouh Ibrahim

2011

Abstract

Clustering in spatial data mining is to group similar objects based on their distance, connectivity, or their relative density in space. In real word, there exist many physical obstacles such as rivers, lakes, highways and mountains, and their presence may affect the result of clustering substantially. Today existing telephone networks nearing saturation and demand for wire and wireless services continuing to grow, telecommunication engineers are looking at technologies that will deliver sites and can satisfy the required demand and grade of service constraints while achieving minimum possible costs. In this paper, we study the problem of clustering in the presence of obstacles to solve network planning problem. In this paper, COD-DBSCAN algorithm (Clustering with Obstructed Distance - Density-Based Spatial Clustering of Applications with Noise) is developed in the spirit of DBSCAN clustering algorithms. We studied also the problem determine the place of Multi Service Access Node (MSAN) due to the presence of obstacles in area complained of the existence of many mountains such as in Saudi Arabia. This algorithm is Density-based clustering algorithm using BSP-tree and Visibility Graph to calculate obstructed distance. Experimental results and analysis indicate that the COD-DBSCAN algorithm is both efficient and effective.

Paper Citation

in Harvard Style

Fattouh Ibrahim L. (2011). ENHANCING CLUSTERING NETWORK PLANNING ALGORITHM IN THE PRESENCE OF OBSTACLES . In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011) ISBN 978-989-8425-79-9, pages 472-478. DOI: 10.5220/0003686304800486

in Bibtex Style

@conference{kdir11,
author={Lamia Fattouh Ibrahim},
title={ENHANCING CLUSTERING NETWORK PLANNING ALGORITHM IN THE PRESENCE OF OBSTACLES},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)},
year={2011},
pages={472-478},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003686304800486},
isbn={978-989-8425-79-9},
}

in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval - Volume 1: KDIR, (IC3K 2011)
TI - ENHANCING CLUSTERING NETWORK PLANNING ALGORITHM IN THE PRESENCE OF OBSTACLES
SN - 978-989-8425-79-9
AU - Fattouh Ibrahim L.
PY - 2011
SP - 472
EP - 478
DO - 10.5220/0003686304800486