A non-uniform clustering method for wireless sensor networks based on the optimal number of clusters

Abstract

The invention discloses a wireless sensor network uneven clustering method based on the optimal clustering number. The wireless sensor network uneven clustering method is characterized by comprising the optimal clustering number calculation method and the uneven clustering method. Firstly, a data compression ratio coefficient is adjusted according to specific conditions, and the position of an aggregation node can be placed at will. Secondly, cluster heads are introduced into the expected value of the aggregation node, the node degree factor is also introduced, so that cluster radius self-adaptive adjustment is realized, the cluster radius of the cluster head close to the aggregation node is decreased so that energy can be saved and used for data aggregation and forwarding, the cluster radius of the cluster head far away from the aggregation node is increased so that more common nodes can be covered, and balanced energy consumption is realized. According to the wireless sensor network uneven clustering method based on the optimal clustering number, the optimization number of the cluster head nodes can be determined accurately, uniform distribution and uneven clustering of the cluster head nodes are realized, energy consumption of the nodes is effectively reduced, the life cycle of a network is prolonged, and the wireless sensor network uneven clustering method is scientific, reasonable, high in practicability, and capable of being widely applied to various wireless sensor networks.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and relates to a method for non-uniform clustering of wireless sensor networks based on the optimal number of clusters. Background technique [0002] Wireless sensor network routing protocol is one of the effective means to optimize network energy consumption. The routing protocols of wireless sensor networks are generally divided into flat routing and hierarchical routing. , the routing table is too large to maintain, and the delay is large; hierarchical routing selects some nodes to do specific tasks, such as collecting common node data, merging and compressing data, packaging and packaging, and then sending to the sink node, etc., to achieve the purpose of optimizing energy consumption. Hierarchical routing can save energy more than planar routing, so it has been paid more attention by researchers. A typical representative of hierarchical routing is the low-power adaptive cl...

AI Technical Summary

Problems solved by technology

In the algorithm, the cluster radius is self-adaptive, and the energy consumption is effectively controlled. However, the selection of the cluster radius only considers the distance from the cluster head node to the sink node, and does not consider other important factors such as node density.

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