Data Collection Algorithm of a 3D Wireless Sensor Network That Weighs Node Coverage Rate and Lifetime

Considering the movement of a sink node in this study to solve the data transmission problem of sensor nodes in a 3D network environment, we propose a Data Collection Algorithm of a 3D wireless sensor network (DCA_3D) that weighs node coverage rate and lifetime. DCA_3D establishes a data collection optimization model that weighs node coverage rate and lifetime with the constraints of the sink node’s moving path selection, data flow, energy consumption, and link transmission. Subsequently, DCA_3D calculates the fitness value of the sink node’s moving path by solving the data collection optimization model with the known sink node’s moving path. Then it uses a modified artificial bee colony algorithm to solve the moving path selection problem of the sink node, and finally obtains the optimal scheme. In the scheme, sink node can find the optimal moving path, whereas the sensor node can find the optimal data communication path. The simulation results show that regardless of the moving path length of the sink node, the maximum data collection hops of the sink node and the number of static sensor nodes change, DCA_3D can find the optimal moving path of the sink node. It can improve the coverage rate of the sensor nodes, the network lifetime and average data transmission amount, and reduce the average energy consumption variance and the average packet loss rate. DCA_3D outperforms the state-of-arts such as RAND, GREED, EDG_3D, and ANT.

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