Multiobjective optimization‐based DV‐hop localization using NSGA‐II algorithm for wireless sensor networks,International Journal of Communication Systems

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Multiobjective optimization‐based DV‐hop localization using NSGA‐II algorithm for wireless sensor networks
International Journal of Communication Systems ( IF 1.7 ) Pub Date : 2020-04-20 , DOI: 10.1002/dac.4431
Vivek Kanwar ₁ , Ashok Kumar ₁

Affiliation

Localization is one of the important requirements in wireless sensor networks for tracking and analyzing the sensor nodes. It helps in identifying the geographical area where an event occurred. The event information without its position information has no meaning. In range‐free localization techniques, DV‐hop is one of the main algorithm which estimates the position of nodes using distance vector algorithm. In this paper, a multiobjective DV‐hop localization based Non‐Sorting Genetic Algorithm‐II (NSGA‐II) is proposed in WSNs. Here, we consider six different single‐objective functions to make three multiobjective functions as the combination of two each. Localization techniques based on proposed multiobjective functions has been evaluated on the basis of average localization error and localization error variance. Simulation results demonstrate that the localization scheme based on proposed multiobjective functions can achieve good accuracy and efficiency as compared to state‐of‐the‐art single‐ and multiobjective GA DV‐hop localization scheme.

中文翻译：

使用NSGA-II算法对无线传感器网络进行基于多目标优化的DV跳定位

定位是无线传感器网络中用于跟踪和分析传感器节点的重要要求之一。它有助于确定事件发生的地理区域。没有位置信息的事件信息没有意义。在无范围定位技术中，DV-hop是使用距离矢量算法估计节点位置的主要算法之一。本文在无线传感器网络中提出了一种基于多目标DV跳定位的非排序遗传算法II（NSGA-II）。在这里，我们考虑六个不同的单目标函数，将三个多目标函数组合为两个。在平均定位误差和定位误差方差的基础上，评估了基于提出的多目标函数的定位技术。

更新日期：2020-04-20

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