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An uneven clustering routing algorithm based on glowworm swarm optimization for wireless sensor networks (UCRA-GSO) is proposed to solve the Wireless sensor network (WSN) energy balance problem. We introduce factors such as cluster head density, cluster head proximity distance, cluster head energy, and compactness of the cluster into a glowworm swarm optimization (GSO) method to find the optimal clustering method. The test case involves a forwarding-tree of two level gradients (single and multi-hop transmission) such that the distance between the sensor and the base station is determined by a cost function. The simulation results show that UCRA-GSO effectively extends the network's life cycle while balancing the network's energy dissipation.

The natural conditions of the deep mine are especially poor and deployment of wireless sensor networks in it is constrained by limited energy and communication resources, Aiming at this problem, a data fusion algorithm based on unbiased gray Markov prediction is proposed to solve this problem. This algorithm uses the unbiased gray Markov prediction model to predict the future data and set the threshold, If the error of the predicted value is within the threshold range, do not send the data, due to the environment in deep coal mine usually relatively stable, so we can reduce the energy consumption by reducing the upload data by using the forecast data. Simulation results shows that the data transfer rate can be reduced under the same threshold, while reducing the energy consumption and extending the network usage time.

A radial increment WSN routing algorithm(RIRA) is proposed to reduce energy consumption and improve transmission efficiency caused by complex environment and narrow tunnel of deep mine, in which the wired network layout is limited. Multi-hop routing methods between clusters can reduce energy consumption. A weighting formula is constructed to select cluster heads, the greater the weight, the more likely to become the final cluster head. The smaller the cluster near Sink, the more the number of clusters, which can share data to the Sink by a number of cluster heads, effectively balancing the energy consumption and ensuring the reliability of data transmission. The simulation results show that the RIRA algorithm can delay the death time of the first node, balance cluster head energy, prolong the network lifetime, and improve robustness of the network.

In order to solve energy-consumption of wireless transmission route, a clustering routing protocol based on improved cellular model is proposed for environmental monitoring through wireless sensor network (WSN) of nuclide leakage in uranium tailings impoundment. The protocol sets the virtual partition of the cellular structure in the monitoring area to reduce complexity of the cluster and to balance the network energy consumption in clustering way. Considering angle ratio and distance ratio between the centroid of the virtual partition and the node when choosing the cluster head, node communication in cluster adopts the method of mixing hop to realize energy balance. Simulation results show that this protocol is not only prolonging the network lifetime effectively, but reducing its energy consumption.