移动无线传感器网络覆盖最大化的萤火虫算法

Eva Tuba, M. Tuba, M. Beko
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引用次数: 29

摘要

无线传感器网络具有广泛的应用,因此是一个活跃的研究领域。传感半径有限的传感器对感兴趣区域的覆盖最大化是一个重要的难优化问题。由于传感器最初通常是随机部署的,解决最大覆盖问题的一种方法是使用移动到最佳位置的移动传感器。由于传感器节点的功率是有限的,传感器节点运动的最小化是次要的优化目标。在本文中,我们提出了一种新的群体智能算法,萤火虫算法,来优化这一困难的多目标问题。我们在标准基准数据上测试了我们的方法,并将结果与文献中的其他技术进行了比较。我们提出的方法更好地考虑了所有质量指标:覆盖范围、能耗、鲁棒性和收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mobile wireless sensor networks coverage maximization by firefly algorithm
Wireless sensor networks have many applications and accordingly represent an active research area. Coverage maximization of the area of interest by sensors that have limited sensing radius is an important hard optimization problem. Since sensors are initially often deployed randomly one way of solving maximal coverage problem is by using mobile sensors that move to optimal positions. Since power in sensor nodes is limited, minimization of the sensor nodes movement is secondary optimization goal. In this paper we propose use of recent swarm intelligence algorithm, firefly algorithm, for optimization of that hard multiobjective problem. We tested our approach on standard benchmark data and compared results with other techniques from literature. Our proposed approach was better considering all quality measures: coverage, energy consumption, robustness and convergence speed.
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