  The cluster formation in Three Dimensional Wireless Sensor Networks (3D-WSN)
give rise to overlapping of signals due to spherical sensing range which leads
to information redundancy in the network. To address this problem, we develop a
sensing algorithm for 3D-WSN based on dodecahedron topology which we call Three
Dimensional Distributed Clustering (3D-DC) algorithm. Using 3D-DC algorithm in
3D-WSN, accurate information extraction appears to be a major challenge due to
the environmental noise where a Cluster Head (CH) node gathers and estimates
information in each dodecahedron cluster. Hence, to extract precise information
in each dodecahedron cluster, we propose Three Dimensional Information
Estimation (3D-IE) algorithm. Moreover, Node deployment strategy also plays an
important factor to maximize information accuracy in 3D-WSN. In most cases,
sensor nodes are deployed deterministically or randomly. But both the
deployment scenario are not aware of where to exactly place the sensor nodes to
extract more information in terms of accuracy. Therefore, placing nodes in its
appropriate positions in 3D-WSN is a challenging task. We propose a Three
Dimensional Node Placement (3D-NP) algorithm which can find the possible nodes
and their deployment strategy to maximize information accuracy in the network.
We perform simulations using MATLAB to validate the 3D-DC, 3D-IE and 3D-NP,
algorithms respectively.
