This paper studies a graph-based sensor deployment approach in wireless sensor networks (WSNs). Specifically, in today's world, where sensors are everywhere, detecting various attributes like temperature and movement, their deteriorating lifetime is indeed a very concerning issue. In many scenarios, these sensors are placed in extremely remote areas, where maintenance becomes challenging. As a result, it is not very wise to depend on a single sensor to obtain data from a particular terrain or place. Hence, multiple sensors are deployed in these places, such that no problem arises if one or few of them fail. In this work, this problem of intelligent placement of sensors is modelled from the graph theoretic point of view. We propose a new sensor deployment approach here, which results in lesser sensor density per unit area and less number of sensors as compared to the existing benchmark schemes. Finally, the numerical results also support our claims and provide insights regarding the selection of parameters that enhance the system performance.

翻译：本文研究无线传感器网络(WSN)中一种基于图的传感器部署方法。具体而言，在传感器遍布各处、检测温度与运动等多种属性的当今世界，其不断缩短的使用寿命确实是一个值得高度关注的问题。在许多应用场景中，这些传感器被部署在极其偏远的区域，使得维护工作变得困难。因此，依赖单一传感器从特定地形或区域获取数据并非明智之举。为此，需要在这些区域部署多个传感器，使得当个别传感器失效时系统仍能正常运行。本研究从图论角度对传感器智能部署问题进行了建模。我们提出了一种新型传感器部署方案，与现有基准方案相比，该方案能降低单位面积的传感器密度并减少传感器总数。最终的数值仿真结果验证了所提方案的有效性，并为提升系统性能的参数选择提供了理论依据。