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首页> 外文期刊>Journal of computational and theoretical nanoscience >Multi Objective Optimization Model for Coverage and Connectivity in Wireless Sensor Networks
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Multi Objective Optimization Model for Coverage and Connectivity in Wireless Sensor Networks

机译：无线传感器网络覆盖与连接的多目标优化模型

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摘要

Due to the technology advancement and increasing in number of interests and requirements, the world is inclining toward reducing the human dependent gradually by increasing the computerized dependents. Nowadays, wireless sensor networks (WSNs) become more interest and more imperative. WSNs have limited resources and there is importance to manage these resources in an optimal manner. Multi objective optimization deals with optimizing many objects simultaneity at same time. These objectives are conflicts in nature, such as coverage, connectivity, life time, number of nodes and energy. In this study, a new algorithm is developed to solve the multi objective optimization problem in WSN based on none dominating sorting genetic algorithm NSGA-II to find the maximized values of two important conflicts issues, the coverage and connectivity as well as the optimal overlapping area, The results in this approach are compared with other author's approaches. Our approach is achieved a good improvement if compared with the previous trails.
机译：由于技术进步和兴趣和要求的数量增加，世界倾向于通过增加计算机化家属逐渐减少人类依赖。如今，无线传感器网络（WSNS）变得更具兴趣和更令人必然。 WSN具有有限的资源，并以最佳的方式重视管理这些资源。多目标优化同时优化许多对象同时性。这些目标是自然界的冲突，例如覆盖，连接，生命时间，节点和能量数量。在本研究中，开发了一种新的算法，以解决WSN中的多目标优化问题，基于无导体分类遗传算法NSGA-II，找到两个重要冲突问题的最大值，覆盖范围和连接以及最佳重叠区域，这种方法的结果与其他作者的方法进行了比较。如果与之前的小径相比，我们的方法是良好的改善。

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