Data aggregation method based on minimum spanning tree

Abstract

The invention discloses a data aggregation method based on a minimum spanning tree. The data aggregation method mainly includes the steps of wireless sensor arrangement, cluster head selection, clustering, simple graph model formation through nodes in clusters, calculation of weight in the clusters, minimum spanning tree building through the nodes in the clusters, aggregation of data in the clusters, cluster head weight calculation, simple graph model formation through nodes in cluster heads, minimum spanning tree building through the nodes in the cluster heads, cluster head data aggregation, node energy consumption balancing and cluster maintaining. According to the data aggregation method, by means of reasonable arrangement of the sensor nodes and clustering of the nodes, energy consumption of the sensor nodes is distributed evenly, the life cycle of a whole wireless sensor network is prolonged, and energy of all the nodes can be used efficiently.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and relates to a data aggregation method among wireless sensors, in particular to the design of a minimum spanning tree-based data aggregation method. Background technique [0002] Wireless sensor network (WSN) is composed of a large number of sensor nodes deployed in the monitoring area, forming a multi-hop self-organizing network system through wireless communication, which measures the thermal, infrared, acoustic Nano, radar and seismic waves and other signals to detect material phenomena including temperature, humidity, noise, light intensity, pressure, speed and direction, and perform functions such as real-time data collection, supervision and control, information sharing and storage management. The energy of sensor network nodes is very limited. Once the energy is exhausted, it will not be replenished in real time. Studies have shown that the energy consumed in the data tr...

AI Technical Summary

Problems solved by technology

The PEGASIS algorithm is based on the fact that the global information of the network can be known by all nodes. In practical applications, there are the following problems: due to limited node capabilities, it is difficult for a single node to save the network; when a node dies unexpectedly, it needs to rebroadcast the global information; fault tolerance Not good, if any node on the PEGASIS chain dies unexpectedly, all data from the chain end to the node will be lost

However, the protocol has serious defects: (1), implosion: a node receives multiple copies of the same data from neighboring nodes at almost the same time; (2), overlap: a node receives almost the same data sent by multiple nodes monitoring the same area Data; (3) Blind utilization of resources: nodes do not consider their own resource limitations, and forward data under any circumstances

[0008] These protocols have certain problems in the selection of cluster heads or in the processing within the cluster, which makes the energy consumption of sensors cannot be well controlled.

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