RWSN中基于aco的路径规划方案

Peng Huang, Zhiliang Kang, Chang Liu, F. Lin
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引用次数: 7

摘要

传统的无线传感器网络是由电池能量有限的传感器节点组成的。由于无线电力传输技术的飞速发展,传感器可以在移动设备的有限充电范围内进行充电,我们将这种网络称为可充电WSN(rechargeable WSN, RWSN)。在RWSN中,采用移动充电器(MC)对传感器节点进行充电。然而,由于单个无线传感器网络的充电功率、移动速度和总能量是有限的,因此寻找最小的无线传感器网络以及如何调度无线传感器网络来完成传感器节点的充电任务成为这种无线传感器网络的主要问题。本文通过对可充电无线传感器网络中MC的路径规划问题进行建模,提出了一种新的路径规划方案——基于蚁群系统的路径规划(ACO_PP)。在ACO_PP算法中,引入虚拟电荷节点为mc创建路由,然后利用蚁群算法对路由进行优化。仿真结果表明,ACO_PP方案比现有方案具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ACO-based path planning scheme in RWSN
Traditional wireless sensor networks (WSNs) are consist of sensor nodes with limited battery energy power. Due to rapid development of wireless power transfer technology, sensors can be recharged when they are within limited charging ranges of mobile devices and we call this kind of network rechargeable WSN(RWSN). In RWSN, mobile chargers (MC) are employed to recharge the sensor nodes. However, since charging power, moving speed and total energy of one MC are limited, finding the minimal MCs and how to schedule the MCs to complete the charging task of the sensor node become the major problems in such RWSNs. In this work, a novel path planning scheme, named ACO_PP (Ant Colony System based path planning), is proposed by modeling the path planning problem of the MC in rechargeable wireless sensor network. In ACO_PP, virtual charge nodes are introduced to create the routes for MCs, and then the Ant Colony Optimization is employed to optimize these routes. The simulation results show that the ACO_PP scheme achieves better performance than existing schemes.
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