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CPAC: Energy-Efficient Algorithm for IoT Sensor Networks Based on Enhanced Hybrid Intelligent Swarm

机译:CPAC:基于增强混合智能群的IOT传感器网络节能算法

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摘要

The wireless sensor network (WSN) is widely employed in the application scenarios of the Internet of Things (IoT) in recent years. Extending the lifetime of the entire system had become a significant challenge due to the energy-constrained fundamental limits of sensor nodes on the perceptual layer of IoT. The clustering routing structures are currently the most popular solution, which can effectively reduce the energy consumption of the entire network and improve its reliability. This paper introduces an enhanced hybrid intelligential algorithm based on particle swarm optimization (PSO) and ant colony optimization (ACO) method. The enhanced PSO is deployed to select the optimal cluster heads for establishing the clustering architecture. An improved ACO is introduced to realize the data transmission from terminal sensor nodes to the base station. Our proposed algorithm can effectively reduce the entire energy consumption and extend the lifetime of IoT sensor networks. Compared with the traditional algorithms, the simulation results show that the presented novel algorithm in this paper has obvious optimization and improvement in network lifetime and energy utilization efficiency.
机译:近年来,无线传感器网络(WSN)广泛采用事物互联网(物联网)的应用方案。由于IOT的感知层上的传感器节点的能量受限基本限制,延伸整个系统的寿命已经成为一个重大挑战。聚类路由结构是目前最流行的解决方案,可以有效地降低整个网络的能耗并提高其可靠性。本文介绍了基于粒子群优化(PSO)和蚁群优化(ACO)方法的增强的混合态算法。部署增强PSO以选择用于建立群集体系结构的最佳群集头。引入改进的ACO以实现从终端传感器节点到基站的数据传输。我们所提出的算法可以有效地降低整个能量消耗并延长IOT传感器网络的寿命。与传统算法相比,仿真结果表明,本文所呈现的新型算法具有明显的网络寿命和能源利用效率的优化和改进。

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