Load‐balanced data gathering in Internet of Things using an energy‐aware cuckoo‐search algorithm,International Journal of Communication Systems

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Load‐balanced data gathering in Internet of Things using an energy‐aware cuckoo‐search algorithm
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2020-03-11 , DOI: 10.1002/dac.4385
Fahimeh Sadeghi ₁ , Avid Avokh ₂

Affiliation

This paper deals with the lifetime problem in the Internet of Things. We first propose an efficient cluster‐based scheme named “Cuckoo‐search Clustering with Two‐hop Routing Tree (CC‐TRT)” to develop a two‐hop load‐balanced data aggregation routing tree in the network. CC‐TRT uses a modified energy‐aware cuckoo‐search algorithm to fairly select the best cluster head (CH) for each cluster. The applied cuckoo‐search algorithm makes the CH role to rotate between different sensors round by round. Subsequently, we extend the CC‐TRT scheme to present two methods for constructing multi‐hop data aggregation routing trees, named “Cuckoo‐search Clustering with Multi‐Hop Routing Tree (CC‐MRT)” and “Cuckoo‐search Clustering with Weighted Multi‐hop Routing Tree (CC‐WMRT).” Both CC‐MRT and CC‐WMRT rely on a two‐level structure; they not only use an energy‐aware cuckoo‐search algorithm to fairly select the best CHs but also adopt a load‐balanced high‐level routing tree to route the aggregated data of CHs to the sink node. However, CC‐WMRT slightly has a better performance thanks to its low‐level routing strategy. As an advantage, the proposed schemes balance the energy consumption among different sensors. Numerical results show the efficiency of the CC‐TRT, CC‐MRT, and CC‐WMRT algorithms in terms of the number of transmissions, remaining energy, energy consumption variance, and network lifetime.

中文翻译：

使用能量感知的布谷鸟搜索算法在物联网中进行负载平衡的数据收集

本文讨论了物联网的生命周期问题。我们首先提出一种有效的基于群集的方案，称为“具有两跳路由树的布谷鸟搜索群集（CC-TRT）”，以开发网络中的两跳负载平衡数据聚合路由树。CC‐TRT使用改良的能量感知布谷鸟搜索算法，公平地为每个群集选择最佳群集头（CH）。应用的布谷鸟搜索算法使CH角色在不同的传感器之间循环旋转。随后，我们扩展了CC-TRT方案，以提供两种构建多跳数据聚合路由树的方法，分别称为“具有多跳路由树的布谷鸟搜索聚类（CC-MRT）”和“具有加权多播的布谷鸟搜索聚类”跃点路由树（CC-WMRT）。” CC‐MRT和CC‐WMRT都依赖于两级结构。他们不仅使用能量感知的布谷鸟搜索算法公平地选择最佳的CH，而且采用负载平衡的高级路由树将CH的聚合数据路由到接收器节点。但是，由于CC-WMRT的底层路由策略，其性能稍有提高。作为优点，提出的方案平衡了不同传感器之间的能量消耗。数值结果显示了CC‐TRT，CC‐MRT和CC‐WMRT算法在传输次数，剩余能量，能耗变化和网络寿命方面的效率。所提出的方案平衡了不同传感器之间的能量消耗。数值结果显示了CC‐TRT，CC‐MRT和CC‐WMRT算法在传输数量，剩余能量，能耗变化和网络寿命方面的效率。所提出的方案平衡了不同传感器之间的能量消耗。数值结果显示了CC‐TRT，CC‐MRT和CC‐WMRT算法在传输数量，剩余能量，能耗变化和网络寿命方面的效率。

更新日期：2020-03-11

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