This paper presents an automated provisioning tool for the deployment of sensors within wireless sensor networks (WSN) where we have employed evolutionary approach as a search technique to find the maximal coverage under minimal deployment cost. The coverage area is partitioned into M by N cells to reduce the search space from continuous to discrete by considering the placement of sensors at the centroid of each cell. The author has explored the relationship between various cell’s sizes versus the total number of deployed sensors. The experimental results show that when the number of cells to cover the service area from X by X cells to 2X by 2X cells is increased, on average this increases the cost by 3 folds. In this regard, it is due to the increase of the number of required sensors by an average of six folds, while improving the coverage ratio by only 9%. A custom-made graphical user interface (GUI) has been developed and embedded within the proposed automated provisioning tool to illustrate the deployment area with the placed sensors at step of the deployment process.
TopMany researchers (Bhardwaj & Chandrakasan, 2002; Haenggi, 2003; Kalpakis, Dasgupta, & Namjoshi, 2002; Krishnamachari & Ordonez, 2003; Pan, Hou, Cai, Shi, & Shen, 2003; Sadagopan & Krishnamachari, 2004) focused their efforts on increasing the lifespan of sensor devices by reducing the coverage. Researchers (Shih, Cho, Ickes, Min, Sinha, Wang, & Chandrakasan, 2001; Woo & Cullar, 2001; Ye, Heidemann, & Estrin, 2002) focused on the physical and media access layers within WSN, where others focused their research on routing and transport protocols (Braginsky & Estrin, 2002; Ganesan, Govidan, Shenkar, & Estrin, 2001; Heinzelman, Chandrakasan, & Balarishnan, 2000). Also, researchers (Bahl & Padmanabhan, 2000; Nicules & Nath, 2003; Savvide, Han, & Strivastava, 2001) focused on localization and position applications of WSN. However, all the above research activities have assumed that the coverage problem is predetermined.