Routing method of double-cluster head wireless sensor network

Abstract

The invention discloses a routing method of a double-cluster head wireless sensor network. The method comprises the following steps: performing network initialization; performing temporary clustering, and collecting the positions and the energy information of intra-cluster ordinary nodes by selected temporary cluster head nodes; selecting out the optimal main cluster head node and the optimal secondary cluster head node by utilizing the particle swarm optimization algorithm according to the information of the intra-cluster ordinary nodes collected by the temporary cluster head nodes and the collection energy consumption and transmission energy consumption minimization criterion; selecting the next-hop node by every secondary cluster head node according to the distance from the secondary cluster head nodes to an aggregation node and the residual energy information at the data transmission stage, and transmitting data to the aggregation node by multiple hops. According to the routing method of the double-cluster head wireless sensor network disclosed by the invention, the problem that loads of cluster heads are overweight can be effectively relieved, the respective energy usage ratios of the two cluster heads are improved, the cluster heads are prevented from rapidly dying, the energy consumption of the network is balanced, and the life cycle of the whole network is prolonged.

Description

technical field [0001] The invention relates to a wireless sensor network routing method, in particular to an energy-saving routing method for a dual-cluster head wireless sensor network based on particle swarm optimization, and belongs to the technical field of wireless sensor networks. Background technique [0002] Wireless sensor network is an important research field in current computer, communication and control disciplines, it provides favorable conditions for people to obtain information. The sensor nodes are small, cheap, easy to conceal and deploy, can be distributed in a large area in the area that needs to be monitored, and can self-organize to form a network. However, the battery energy of sensor nodes is limited, and in most cases, the nodes cannot be charged or replaced. Once the energy of the nodes is used up, it means that the nodes die and the network operation is affected. Therefore, designing a low-energy wireless sensor network routing method is the curre...

AI Technical Summary

Problems solved by technology

The first category, such as LEACH, EEUC, cluster heads are generated randomly. Although this method can effectively prevent a node from becoming a cluster head continuously and delay node death, the number of cluster heads generated in each round is not fixed, which may easily cause the cluster range to be too large. Or too small, it is difficult to balance network energy consumption

The second category, such as HEED and CHTD, is a completely distributed clustering algorithm that dynamically generates more reasonable cluster heads through information interaction between nodes, but the information interaction process requires a large number of broadcast messages, resulting in additional energy overhead

The third type, such as LEACH-C and BCDCP, each node reports information such as its geographical location and current energy to the sink node, and the sink node selects the appropriate cluster head according to the global information and divides the clusters reasonably, but this type of method requires the sink node Understand the global information

[0005] Aiming at the problem that the cluster head load of the clustering routing algorithm in the prior art is too heavy, the energy utilization rate is not high and the network death is accelerated, based on the principle of minimizing the energy consumption of collection and transmission, a new particle swarm optimization wireless sensor network dual The cluster head energy-saving routing method is of great significance to effectively alleviate the overload of the cluster head, improve the energy utilization rate of the cluster head, and prolong the survival time of the network.

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