摘要
为了高效利用有限的无线传感器网络节点能量,延长网络的生命周期,提出了一种应用于无线传感器网络协议中的改进引力搜索算法(IMPGSA)来更新簇头节点的位置。该算法使用分数阶微积分对引力搜索算法(GSA)进行优化,使用多目标适应度函数对簇头节点更新后的位置进行评估,这些目标包括距离、延迟、链路生命周期和能量。仿真结果表明:本文提出的改进算法与人工蜂群算法(ABC)、引力搜索算法(GSA)和粒子群免疫协同算法(MPSICA)相比,网络生命周期分别提高了10.7%、22.4%和13.1%。可见,该算法通过在网络中不断进行迭代以更新簇头节点的位置,有效延长了网络节点的生命周期,进而有效延长了网络本身的生命周期。
Aiming at the high-efficient utilization of the limited energy of sensor nodes to extend the network life cycle, an improved gravitational search algorithm(IMPGSA) used in wireless sensor network protocol is proposed to update the position of cluster head nodes. The fractional calculus is adopted to optimize the gravitational search algorithm(GSA), and the multi-objective fitness function is selected to evaluate the updated position of cluster head nodes, which includes distance, delay, link life cycle and energy. The simulation results indicate that compared with the artificial bee colony(ABC), the gravitational search algorithm(GSA) and the multi-particle swarm immune coordination algorithm(MPSICA), the proposed algorithm of this paper has improved the network life cycle by 10.7%, 22.4% and 13.1% respectively. By iterating, the position of cluster head nodes is updated in the network, the life cycle of network nodes is extended and accordingly the life cycle of network itself is prolonged.
作者
万振凯
贾思禹
WAN Zhen-kai;JIA Si-yu(Informatization Center,Tianjin Polytechnic University,Tianjin 300387,China;School of Computer Science andTechnology,Tianjin Polytechnic University,Tianjin 300387,China)
出处
《天津工业大学学报》
CAS
北大核心
2019年第3期66-73,共8页
Journal of Tiangong University
基金
天津市教委社会科学资助项目(2017JWZD28)
关键词
无线传感器网络
引力搜索算法
分数阶微积分
多目标适应度函数
wireless sensor networks(WSN)
gravitational search algorithm(GSA)
fractional calculus
multi-objective fitness function
