School of Electrical and Computer Engineering, Pusan National University, Busan 46241, Korea.
Sensors (Basel). 2020 Jul 3;20(13):3733. doi: 10.3390/s20133733.
This paper proposes a sensor node activation method using the nature-inspired algorithm (NIA) for the target coverage problem. The NIAs have been used to solve various optimization problems. This paper formulates the sensor target coverage problem into an object function and solves it with an NIA, specifically, the bat algorithm (BA). Although this is not the first attempt to use the BA for the coverage problem, the proposed method introduces a new concept called bat couple which consists of two bats. One bat finds sensor nodes that need to be activated for sensing, and the other finds nodes for data forwarding from active sensor nodes to a sink. Thanks to the bat couple, the proposed method can ensure connectivity from active sensor nodes to a sink through at least one communication path, focusing on the energy efficiency. In addition, unlike other methods the proposed method considers a practical feature of sensing: The detection probability of sensors decreases as the distance from the target increases. Other methods assume the binary model where the success of target detection entirely depends on whether a target is within the threshold distance from the sensor or not. Our method utilizes the probabilistic sensing model instead of the binary model. Simulation results show that the proposed method outperforms others in terms of the network lifetime.
本文提出了一种使用基于自然启发式算法(NIA)的传感器节点激活方法,用于解决目标覆盖问题。NIA 已被用于解决各种优化问题。本文将传感器目标覆盖问题表述为目标函数,并使用 NIA(具体来说是蝙蝠算法(BA))来解决它。虽然这不是第一次尝试将 BA 用于覆盖问题,但所提出的方法引入了一个新的概念,称为蝙蝠对,它由两只蝙蝠组成。一只蝙蝠找到需要激活进行感测的传感器节点,另一只蝙蝠找到从活动传感器节点到汇聚节点的数据转发节点。由于蝙蝠对,所提出的方法可以确保从活动传感器节点到汇聚节点的连接性,至少通过一条通信路径,重点是提高能量效率。此外,与其他方法不同,所提出的方法考虑了感测的实际特征:随着与目标距离的增加,传感器的检测概率会降低。其他方法假设二进制模型,其中目标检测的成功完全取决于目标是否在传感器的阈值距离内。我们的方法使用概率感测模型而不是二进制模型。仿真结果表明,在所提出的方法在网络寿命方面优于其他方法。