Abstract
The cold and arid regions of China occupy a large proportion of the total land area, are rich in resources and have a prominent strategic position, but their fragile ecological environment seriously affects the information collection and lifecycle of the field observation instrument network (FOIN), which affects the in-depth research for cold and arid regions. To balance the energy consumption and improve performance of the FOIN, an area autonomous routing protocol based on multi-objective optimization methods for FOIN (FOI-MOC) was proposed Firstly, in the network preparation stage, the FOI-MOC algorithm calculates the number of optimal cluster heads, evenly partitions for FOIN, and allocates the number of regional cluster heads. Then, in the cluster establishment stage, the different objective functions are constructed based on the residual energy, distance, and density of nodes in their respective regions. Multi-objective optimization algorithms, NSGAII and PSO are utilized to address the Pareto optimal solution set The Pareto optimal solution set is scored by dynamically assigning weights to each objective function through the entropy method, and final cluster heads are elected for each region. Finally, in the data transmission stage, single-hop transmission is adopted within clusters, and single-hop or multi-hop transmission is employed between clusters according to the distance between cluster head and base station. The experimental results indicate that the developed protocol based on multi-objective optimization methods can efficiently balance network energy consumption and prolong network lifecycle.
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