Scene adaptive energy balance-based sensor network vector quantization clustering method
A sensor network, energy balancing technology, applied in network traffic/resource management, network planning, network topology, etc., can solve problems such as shortening network life, achieve the effect of improving life cycle, balancing energy and load
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Embodiment 1
[0030] This embodiment is based on the figure 2 The network topology shown is illustrated. It mainly explains the clustering method when the sink node is far away from the event source. The application network model is as follows:
[0031] 100 sensor nodes are randomly distributed in an area of 100m×100m, the network has the following properties:
[0032] The sensor network node is a static non-moving node; the sink node is at (150, 50); the energy of the sink node is not limited, and the geographical location information and initial energy information of the network node can be obtained. For simplicity, set the event source at the center of the region (50, 50). The topological distribution of sensor nodes and sink nodes is as follows: figure 2 shown.
[0033] Assuming that all nodes in the event source perception area report information to the sink node, the information distortion degree of the sink node is the smallest. In the process of dividing the cluster area and...
Embodiment 2
[0050] This embodiment is based on the image 3 The network topology shown is illustrated. It mainly explains the clustering method when the sink node is close to the event source. The application network model is as follows:
[0051] 100 sensor nodes are randomly distributed in an area of 100m×100m, the network has the following properties:
[0052] The sensor network node is a static non-moving node; the sink node is at (50, 50) position; the energy of the sink node is not limited, and the geographical location information and initial energy information of the network node can be obtained. For simplicity, set the event source at the center of the region (50, 50). The topological distribution of sensor nodes and sink nodes is as follows: image 3 shown.
[0053] The distortion degree of the information received by the sink node is measured by the following formula:
[0054] D E ( M ) ...
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