论文标题
障碍室内环境中移动传感器节点的覆盖范围和能量分析：沃罗诺伊方法
Coverage and Energy Analysis of Mobile Sensor Nodes in Obstructed Noisy Indoor Environment: A Voronoi Approach
论文作者
论文摘要
无线传感器网络（WSN）的快速部署构成了寻找网络节点最佳位置的挑战，尤其是在（i）未知和（ii）障碍物富裕环境中。本文通过野牛（由生物启发的自组织网络）解决了这一挑战，这是Voronoi算法的变体。与方案挑战相一致，野牛节点仅限于（i）在本地感知的以及（ii）嘈杂的信息，以避免障碍，避免障碍并与邻近的节点联系。绩效被衡量为（i）覆盖面积的百分比，（ii）节点传播的总距离，（iii）累积能量消耗和（iv）节点分布的均匀性。系统地研究了障碍星座和噪声水平，并提出了用于失败节点的无冲突恢复策略。从广泛的模拟中获得的结果表明，算法在融合速度和部署成本上都超过了先前报道的方法。
The rapid deployment of wireless sensor network (WSN) poses the challenge of finding optimal locations for the network nodes, especially so in (i) unknown and (ii) obstacle-rich environments. This paper addresses this challenge with BISON (Bio-Inspired Self-Organizing Network), a variant of the Voronoi algorithm. In line with the scenario challenges, BISON nodes are restricted to (i) locally sensed as well as (ii) noisy information on the basis of which they move, avoid obstacles and connect with neighboring nodes. Performance is measured as (i) the percentage of area covered, (ii) the total distance traveled by the nodes, (iii) the cumulative energy consumption and (iv) the uniformity of nodes distribution. Obstacle constellations and noise levels are studied systematically and a collision-free recovery strategy for failing nodes is proposed. Results obtained from extensive simulations show the algorithm outperforming previously reported approaches in both, convergence speed, as well as deployment cost.
