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An example for cooperative sensor fusion is stereovision.
The corresponding framework of the cooperative sensor network is shown in Figure 3.
A node which holds more residual energy and close to the cooperative sensor node has a higher probability to become a CH.
Figure 3 Underlying graph of the cooperative sensor network shown in Fig. 2. The nodes 1, 2, and 3 correspond to three anchor nodes.
In real life cooperative sensor network scheme, nodes can spend a high percent of their energy for relaying packets from other nodes.
For example, for the cooperative sensor network shown in Figure 2 to be localizable, the underlying graph of the sensor network shown in Figure 3 should be globally rigid [18].
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Here, N R is the scale of cooperative sensors.
These adaptive algorithms are then used for blind estimation in a wireless sensor network using diffusion of data among cooperative sensors.
The throughput with wireless sensor networks could be obtained by Eq. (11), where N R is the scale of cooperative sensors.
There are three phases in the progress of constructing the hierarchical cooperative transmission network, which are as follows: The first stage: to establish the collection of hierarchical cooperative sensors.
Wireless sensor networks (WSN) consist of autonomous, cooperative sensors spatially deployed over a geographical area, with applications ranging from surveillance [1] and localization systems [2, 3], to environmental monitoring for physical field sensing and disaster prevention [4, 5].
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