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首页> 外文期刊>International journal of communication systems >A distributed swarm intelligence-based energy-saving method among massive edge nodes
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A distributed swarm intelligence-based energy-saving method among massive edge nodes

机译：大规模边缘节点中的分布式群体基于智能的节能方法

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摘要

In edge computing, how to save energy among sustainable edge nodes is a hot topic. ON/OFF switching of edge nodes as a key point is efficient but still suffers from the long round-trip time problem because of its centralized control manner. Especially in the wireless network, service coverage is proved to be NP-Complete. To this end, we propose a Distributed Swarm intelligence-based Energy-saving algorithm (DSE). In DSE, pheromone and residual energy are used to calculate the wake-up probability. Through the wake-up probability, the edge node can be activated periodically and efficiently. In order to balance the energy in the whole system that contains massive edge nodes, we further use a correction factor, that is, DSE+, to adjust the wake-up probability of the nodes. The proposed methods allow for distributed implementation without requiring a centralized control by the coordinator, and the pheromone accumulated temporally and spatially. In addition, they do not require node localization. Experiments show that both DSE and DSE+ can work as expected, and DSE+ with the correction factor improves the lifetime of the whole system at least 12.6% compared with the DSE without the correction factor.
机译：在边缘计算中，如何在可持续边缘节点之间节省能量是一个热门话题。边缘节点的开/关切换为关键点是有效的，但由于其集中控制方式，仍然存在长的往返时间问题。特别是在无线网络中，证明服务覆盖范围是NP完整的。为此，我们提出了一种分布式群体基于智能的节能算法（DSE）。在DSE中，信息素和残留能量用于计算唤醒概率。通过唤醒概率，可以周期性和有效地激活边缘节点。为了平衡包含大量边缘节点的整个系统中的能量，我们进一步使用校正因子，即DSE +，调整节点的唤醒概率。所提出的方法允许分布式实施，而不需要由协调器的集中控制，并且信息素在时间和空间上累积。此外，它们不需要节点本地化。实验表明，DSE和DSE +可以按预期工作，而DSE +与校正因子的校正+与没有校正因子的DSE相比，整个系统的寿命至少12.6％。

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