Chih-Ning Huang and Chia-Tai Chan / Procedia Computer Science 5 (2011) 58–6563

where E’ is the modified Euclidean distance by adjusted RSSI. Equation (5) means the reference node with smallest Euclidean distance has largest weight.

4.Experimental Results and Discussion

Fig. 3. The deployment and experimental environment

The experiment is done in a 11m (length) × 5.75m (weight) classroom. As shown in Figure 3, the gateway is at the middle and the 18 reference nodes are averagely fixed in the classroom between 2m. Besides, five RF generators are set symmetrically between reference nodes. We put mobile node at the coordinates A (1.5, 1.875), B (3.5, 1.875),

C (5.5, 1.875) and D (7.5, 1.875) respectively. The error distance, e, can show the performance by the mobile node’s coordinate (x0, y0) and estimation result (x, y) is defined as e x x02 y y02. (6)

4.1.The number of nearest reference node(s)

One of the key issues affecting the estimation position is to determine the optimal number p of nearest reference node(s) for Equation (4). Figure 4 shows the average, maximum and minimum values of error distance at four positions, A, B, C and D, for p is from 1 to 18, and the standard deviations are also shown on the average line. No matter it is average, maximum or minimum values of error distance, the smallest error distance occurs when p

= 4,

and it is worthy to note the accuracy results conforms to that of previous studies for LANDMARC methodology

[5][9].

Fig. 4. The error distance v.s. p-nearest reference nodes