A Data Fusion Method for Wireless Sensor Networks Based on Hybrid Delay Sensitive Clustering

Abstract

The invention discloses a wireless sensor network data fusion method for mixed time-delay sensitive clustering. The sensor nodes of the invention form an exponentially increasing cluster structure through an energy efficient clustering algorithm. The data is fused and processed, and then transmitted to the sink through TDMA. In the algorithm, there are two ways of single-layer and multi-layer connections between cluster heads and cluster members. A decision function is proposed, which compares the time delay and energy consumption corresponding to the single-layer and multi-layer models in a weighted manner, and decides the clustering method of each cluster to achieve the optimal trade-off between time delay and energy consumption. In the clustering stage, the energy-efficient clustering algorithm considers the node density and physical location, and selects the node with the smallest cost value as the cluster head by constructing a cost function, so as to shorten the communication distance. After the network has been running for a period of time, in order to balance the energy consumption load of the nodes, the dynamic cluster head reselection algorithm is used to construct a benefit function in the cluster to re-election for a new cluster head.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor networks, and in particular relates to a technical method for constructing a delay-sensitive routing algorithm of a wireless sensor network. Background technique [0002] Since wireless sensor networks (WSNs) are usually deployed in unattended environments, it is almost impossible to replace the batteries of sensor nodes when they run out of energy. Therefore, how to implement complex data monitoring and information reporting on sensor nodes with limited energy is the primary problem to be solved in WSNs. It has been proved that the transmission energy consumption between sensor nodes is much higher than the calculation energy consumption within the node. Therefore, it is very important to propose a method to reduce the amount of data transmission between sensor nodes and thereby reduce the energy consumption of the network. Sensor network data fusion (data fusion) technology can well so...

AI Technical Summary

Problems solved by technology

However, most of the algorithm network models are fixed, and cannot be adaptively adjusted for different fusion rates, lacking universal applicability

At the same time, the reduction in latency is often at the expense of energy consumption, which makes many networks perform poorly in terms of energy saving

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