Method for combining data collection and energy supply in WRSNs (Wireless Rechargeable Sensor Networks)
A technology of energy supply and joint data, applied in power management, electrical components, transmission systems, etc., to achieve the effect of energy supply balance and burden reduction
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Embodiment 1
[0068] Such as figure 1 As shown, a method for joint data collection and energy supply in WRSNs, comprising the following steps:
[0069] (1) Determine the communication radius r of the node and the charging radius R of the mobile charger;
[0070] (2) Determine the number C of clusters in the network according to the charging radius R of the mobile charger, use the K-means method to cluster the network, and determine the node that serves as the first round of cluster heads, and the first round of parking in each cluster The point is also the aforementioned cluster head node;
[0071] Wherein, the calculation formula of the number C of the clusters is:
[0072]
[0073] Among them, L is the side length of the monitoring area, R is the charging radius of the mobile charger, and r is the communication radius of the node.
[0074] The method for determining the node serving as the cluster head in the first round is: selecting the node closest to the cluster center in each c...
Embodiment 2
[0120] In the case that the node communication radius is r and the charging range of the charger is R, the network adopts the K-means method to cluster, and the number of clusters is according to the formula: Obtained, the result of clustering is as follows figure 2 shown.
[0121] During the first round of data collection, the cluster head of each cluster is assumed by the node closest to the cluster center. After one round, the cluster head node of each cluster is selected according to the formula:
[0122]
[0123] where E resi (n) is the remaining energy of node n, E aver is the average remaining energy of the nodes in the cluster, d aver is the average distance from the nodes in the cluster to the parking point of the charger, d(n) is the distance from node n to the parking point, and α represents a threshold; after one round, the one with the larger value of C(n) is selected as the cluster head.
[0124] For data collection, a greedy routing and forwarding mecha...
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