Cluster head node selection method and clustering method of wireless sensor network

Abstract

The invention discloses a cluster head node selection method of a wireless sensor network, belonging to the technical field of wireless sensor networks. The present invention aims at defects in the prior art, when cluster head nodes are selected, influence of position distribution and residual energy of the nodes on the life cycle of the whole network is comprehensively considered, and position information and residual energy information of the nodes are fused to quantized priority parameters by utilizing a fuzzy algorithm, so that more reasonable selection of the cluster head nodes is implemented. The invention also discloses a clustering method of the wireless sensor network, the cluster head nodes are selected by utilizing the method, and dynamic regulation is carried out on the cluster head nodes in a self-adaptive manner according to the energy consumption condition of the cluster head nodes. In comparison with the prior art, the cluster head node selection method and the clustering method of the wireless sensor network have the advantages of capability of effectively improving the life cycle of the wireless sensor network and simpler algorithm.

Description

technical field [0001] The invention relates to a wireless sensor network cluster head node selection method and a clustering method, belonging to the technical field of wireless sensor networks. Background technique [0002] In wireless sensor networks, measuring the life cycle of a sensor network is usually determined according to the remaining energy of nodes. The life cycle of a sensor network is from the time when the network starts to work until the energy of the nodes appearing in it returns to zero. Therefore, in order to prolong the life cycle of the entire sensor network, it is extremely important to reasonably control the energy consumption of nodes. [0003] According to the network topology, the node provides message receiving and forwarding services for the neighbor nodes in the current transmission domain. With the transmission of data traffic, the energy consumption of the wireless transceiver of the node and the idle time overhead of the communication modul...

AI Technical Summary

Problems solved by technology

In the LEACH algorithm, the probability of each node becoming a cluster head is almost equal, so the LEACH algorithm achieves a good energy balance in terms of node energy, but the shortcoming of this algorithm is that it does not consider the geographical location of the cluster head node. Moreover, the distribution of cluster heads is uneven, so it is possible that the distance between two cluster heads exceeds the maximum communication range of nodes, which may cause the entire backbone network to fail to form

[0008] In summary, the existing cluster head selection algorithms generally have the disadvantages of single consideration factors and failure to prolong the life cycle of wireless sensor networks to the greatest extent.

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