Mine environment wireless sensor network clustering routing protocol based on K-means (CRPK-means)

Abstract

The invention provides a mine environment wireless sensor network clustering routing protocol based on K-means (CRPK-means). The method comprises the following steps: acquiring sensor node geographiclocation information under long-distance banded region, forming multiple uniform clusters by using a K mean value clustering algorithm, and then electing the node closest to the centroid as the initial cluster head; and then adopting a dynamic cluster head rotation method, and finally transmitting the data by dynamically selecting a mixed transmission way of single-hop and multi-hop according to the distance between the cluster head and a base station and the distance between the cluster head and the cluster head at an integrated data transmission stage, wherein the turn is not used as the unit to perform re-clustering once the clustering is established, and only the cluster head dynamic change based on residual energy and geographical location is performed at each turn. Compared with thetraditional low energy adaptive clustering hierarchy routing protocol (LEACH), the method can balance the network load more effectively, the life cycle of the whole network is prolonged, and the method is superior to the traditional LEACH protocol method under the same condition.

Description

technical field [0001] The invention belongs to the field of wireless sensor networks, and in particular relates to a clustering routing method for mine environment wireless sensor networks based on K-means. Background technique [0002] In recent years, major mine accidents have occurred frequently, causing huge losses of state property and citizens' lives. Mine safety production and emergency rescue have become the focus of social attention. Because the Wireless Sensor Network (WSN) has the advantages of convenient deployment, low cost, flexible structure and strong invulnerability, it is especially suitable for comprehensive monitoring in underground mines. Introducing WSN into the coal mine safety monitoring system, using its self-organization and wireless communication characteristics, can effectively realize the monitoring of safety production blind spots that cannot be reached by wired monitoring systems and post-disaster data collection, which is very good for exist...

AI Technical Summary

Problems solved by technology

However, the algorithm selects cluster heads according to the threshold formula in each round, which has great randomness. The number of cluster heads elected in each round is uncertain, and the distribution range is random, which leads to uneven energy consumption of nodes and premature death.

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