基于一种新型优化模型的频谱感知分簇算法

Spectrum Aware Clustering Algorithm Based on a NovelOptimization Model

为缓解频谱资源紧缺的现状,对认知无线传感器网络(Cognitive Radio Sensor Network,CRSN)进行了深入研究。切尔诺贝利灾难优化器(Chernobyl Disaster Optimizer,CDO)作为一种新型优化模型,具有收敛性能较强、结构简单和需要调节的参数少等优点。为提高CRSN能效,延长CRSN的生存周期,提出了一种基于量子切尔诺贝利灾难优化器的频谱感知分簇算法(Quantum Chernobyl Disaster Optimizer-based Spectrum Aware Clustering Algorithm,QCDOC)。QCDOC的主要目标是通过最小化节点之间的通信距离来提高网络的生存周期。QCDOC通过为CDO引入量子旋转门和量子非门来增强其搜索能力,采用二进制种群编码以使其适用于簇头(Cluster Head,CH)选举问题。QCDOC在设计适应度函数时考虑了节点剩余能量、距离和频谱可用性,提高了算法的能效。实验表明,与对比算法相比,QCDOC算法具有更长的生存周期、更多的数据传输量和更均衡的网络能耗。

Cognitive Radio Sensor Network(CRSN)has been intensively studied in order to alleviate the shortage of spectrum resources.Chernobyl Disaster Optimizer(CDO),as a novel optimization model,has advantages of strong convergence performance,simple structure,and fewer parameters to be adjusted.To improve the energy efficiency of CRSN and prolong the lifetime of CRSN,this paper proposes a Quantum Chernobyl Disaster Optimizer-based Spectrum Aware Clustering Algorithm(QCDOC).The main goal of QCDOC is to improve the lifetime of network by minimizing the communication distances between nodes.QCDOC introduces quantum rotating gates and quantum non-gates for CDO to enhance searching capability,and employs a binary population encoding to make it suitable for the Cluster Head(CH)election problem.QCDOC considers the residual energy of nodes,distance and spectrum availability while designing a fitness function to improve the energy efficiency of algorithm.Experiment results show that the QCDOC algorithm has longer lifetime,more data transmission and more balanced network energy consumption than comparison algorithms.