Improved GAF (geographical adaptive fidelity) topology design method for wireless sensor network

Abstract

The invention discloses an improved GAF (geographical adaptive fidelity) topology design method for a wireless sensor network. An energy acquisition module and a network topological structure control module are adopted, the sensor network is divided into a plurality of large areas, each large area is internally divided into a plurality of small areas, each small area stands for a small cluster, a small area cluster head is selected according to a cluster head election method while other nodes enters a sleep state, each large area stands for a large cluster, and a large cluster head is selected from multiple small cluster heads to perform information packaging and transmission. Nodes of the small areas transmit information to active nodes in the areas, the information is packaged through the active nodes and then transmitted to cluster heads of the large areas correspondingly, and the information is packaged by the cluster heads and transmitted to a base station. Life cycles of the nodes are prolonged, balancing of node energy states is realized, and relative stability of a node system is realized consequently.

Description

technical field [0001] The invention relates to the technical field of wireless communication, in particular to a design method of an improved GAF ​​topology of a wireless sensor network. Background technique [0002] The GAF (geographical adaptive fidelity) algorithm is a routing algorithm based on geographic location as the basis for clustering. It was later applied to the WSN wireless sensor network, adding a node sleep mechanism, and became a classic clustering energy-saving routing algorithm for wireless sensor network devices. The GAF algorithm divides the detection area into several virtual unit grids. Each virtual grid elects a cluster head node through its cluster head election mechanism, and other nodes in the same virtual grid enter a sleep state to reduce energy consumption. [0003] As a classic energy-saving clustering routing algorithm, the GAF algorithm still has many points to be improved. The main problems are as follows: (1) The cluster head election mecha...

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Problems solved by technology

[0003] As a classic energy-saving clustering routing algorithm, the GAF algorithm still has many points to be improved. The main problems are as follows: (1) The cluster head election mechanism in the GAF algorithm does not consider the energy state of each node in the unit virtual grid. Instead, the cluster head is randomly selected, which will cause too many nodes to elect to become cluster heads, the cluster head processing tasks are heavy, and the energy consumption is too fast, while the nodes that are rarely elected as cluster heads are often in a sleep state, and the remaining energy is sufficient. Node load balancing, some nodes die early

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