An Energy-Saving Hybrid-Optimization Scheduling Algorithm Based on Fat Tree in WSN
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초록
In the data scheduling process of wireless sensor network (WSN), node data fusion is one of the main methods to reduce network communication volume. The decrease in network communication volume contributes to the network energy consumption reduction, which is crucial for improving the WSN lifecycle. Hence, we propose an energy-saving hybrid-optimization scheduling algorithm based on fat tree (FT) for WSN, which is referred to as the FTEBHSA algorithm. In the scheduling algorithm, multiple strategies are adopted to optimize for saving energy, involving shortest path tree optimization, fusion tree load balance, a fusion node rotation mechanism, and a sleep mechanism for monitoring nodes. More importantly, we introduce the FT structure to organically integrate these strategies for reducing the energy consumption and boosting the WSN lifecycle. The simulation experiment results verify that the proposed hybrid-optimization scheduling algorithm performs optimally in optimizing the energy consumption.
Abstract
In the data scheduling process of wireless sensor network (WSN), node data fusion is one of the main methods to reduce network communication volume. The decrease in network communication volume contributes to the network energy consumption reduction, which is crucial for improving the WSN lifecycle. Hence, we propose an energy-saving hybrid-optimization scheduling algorithm based on fat tree (FT) for WSN, which is referred to as the FTEBHSA algorithm. In the scheduling algorithm, multiple strategies are adopted to optimize for saving energy, involving shortest path tree optimization, fusion tree load balance, a fusion node rotation mechanism, and a sleep mechanism for monitoring nodes. More importantly, we introduce the FT structure to organically integrate these strategies for reducing the energy consumption and boosting the WSN lifecycle. The simulation experiment results verify that the proposed hybrid-optimization scheduling algorithm performs optimally in optimizing the energy consumption.
