基于改进猫群算法的物联网感知层路由优化策略
|
摘要
针对物联网感知节点能量受限造成的数据传输瓶颈问题,提出一种基于改进猫群算法的路由优化策略。通过对猫群优化算法进行改进,根据迭代次数、路径节点能量与适应度值动态调整猫的分配率、记忆池和惯性权重,使其具有动态自适应性。在生成路径时综合考虑路径剩余能量方差、节点能量、节点负载、节点间距离等因素,并引入备份路由思想,保证数据传输的实时性。仿真结果表明,该优化策略能够有效减少最优路径建立时间并均衡网络能耗,延长物联网感知层网络的生命周期。
Aiming at the bottleneck of data transmission caused by the energy limitation of sensor nodes in Internet of Things(IoT),this paper proposes a routing optimization strategy based on improved Cat Swarm Optimization(CSO).The cat swarm optimization algorithm is improved. Each cat changes its own MR,SMP and inertia weight dynamically in each iteration process based on the number of iterations,energy of the path nodes and fitness. When the path is generated,path residual energy variance,node energy,node load,node distance four factors are taken into account,and the idea of backup routing is introduced to ensure the real time. Simulation results show that the optimization strategy can effectively reduce the optimal path construction time and balance the network energy consumption,and prolong the life cycle of the perception layer network of the IoT.
Aiming at the bottleneck of data transmission caused by the energy limitation of sensor nodes in Internet of Things(IoT),this paper proposes a routing optimization strategy based on improved Cat Swarm Optimization(CSO).The cat swarm optimization algorithm is improved. Each cat changes its own MR,SMP and inertia weight dynamically in each iteration process based on the number of iterations,energy of the path nodes and fitness. When the path is generated,path residual energy variance,node energy,node load,node distance four factors are taken into account,and the idea of backup routing is introduced to ensure the real time. Simulation results show that the optimization strategy can effectively reduce the optimal path construction time and balance the network energy consumption,and prolong the life cycle of the perception layer network of the IoT.
引文
[1]张生益,陈俊杰,张军朝.基于SDH/MSTP的煤矿物联网设计[J].太原理工大学学报,2012,43(5):564-568.
[2]张鸿亮,刘文予,符明丽.基于需求等级的传感器网络安全策略模型[J].微计算机信息,2018,24(13):134-136.
[3]吴笛,董淑福,王建峰,等.WMSNs中粒子群优化的多径流量分配路由算法[J].空军工程大学学报(自然科学版),2015,16(1):72-76.
[4]朱永红,丁恩杰,胡延军.PSO优化的能耗均衡WSNs路由算法[J].仪器仪表学报,2015,36(1):78-86.
[5]刘章,谭阳.改进遗传算法的WSN节点最优路由选择策略[J].计算机工程与应用,2015,51(13):101-105.
[6]岳亚南,张国良,陈坚.基于能量均衡的节点最优路由选择策略[J].计算机仿真,2015,32(07):268-272.
[7]肖铖,孙子文.基于蚁群系统的WSN能量均衡多路径路由协议[J].计算机工程与设计,2015,36(7):1695-1700.
[8]KONG L,CHEN C M,SHIH H C,et al.An energy-aware routing protocol using cat swarm optimization for wireless sensor networks[M].Berlin,Germany:Springer,2014.
[9]KONG L,PAN J S,TSAI P W,et al.A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network[J].International Journal of Distributed Sensor Networks,2015(2015):1-10.
[10]张卿,谢志鹏,凌波,等.一种传感器网络最大化生命周期数据收集算法[J].软件学报,2005,16(11):1946-1957.
[11]HEINZELMAN W B,CHANDRAWASAN A P.An application-specific protocol architecture for wireless microsensor networks[J].IEEE Transactions on Wireless Communications,2000,4(1):660-670.
[12]CHU S C,TSAI P,PAN J S.Cat swarm optimization[J].Lecture Notes in Computer Science,2006(6):854-858.
[13]CHU S C,TSAI P W.Computational intelligence based on the behavior of cats[J].International Journal of Innovative Computing Information and Control Ijicic,2007,3(1):163-173.
[14]李淑梅,庄铭杰,庄弘.二进制描群算法在大规模MIMO天线选择中的应用[J].电讯技术,2017(6):698-702.
[15]马知也,施秋红.猫群算法研究综述[J].甘肃广播电视大学学报,2014(2):41-45.
[2]张鸿亮,刘文予,符明丽.基于需求等级的传感器网络安全策略模型[J].微计算机信息,2018,24(13):134-136.
[3]吴笛,董淑福,王建峰,等.WMSNs中粒子群优化的多径流量分配路由算法[J].空军工程大学学报(自然科学版),2015,16(1):72-76.
[4]朱永红,丁恩杰,胡延军.PSO优化的能耗均衡WSNs路由算法[J].仪器仪表学报,2015,36(1):78-86.
[5]刘章,谭阳.改进遗传算法的WSN节点最优路由选择策略[J].计算机工程与应用,2015,51(13):101-105.
[6]岳亚南,张国良,陈坚.基于能量均衡的节点最优路由选择策略[J].计算机仿真,2015,32(07):268-272.
[7]肖铖,孙子文.基于蚁群系统的WSN能量均衡多路径路由协议[J].计算机工程与设计,2015,36(7):1695-1700.
[8]KONG L,CHEN C M,SHIH H C,et al.An energy-aware routing protocol using cat swarm optimization for wireless sensor networks[M].Berlin,Germany:Springer,2014.
[9]KONG L,PAN J S,TSAI P W,et al.A balanced power consumption algorithm based on enhanced parallel cat swarm optimization for wireless sensor network[J].International Journal of Distributed Sensor Networks,2015(2015):1-10.
[10]张卿,谢志鹏,凌波,等.一种传感器网络最大化生命周期数据收集算法[J].软件学报,2005,16(11):1946-1957.
[11]HEINZELMAN W B,CHANDRAWASAN A P.An application-specific protocol architecture for wireless microsensor networks[J].IEEE Transactions on Wireless Communications,2000,4(1):660-670.
[12]CHU S C,TSAI P,PAN J S.Cat swarm optimization[J].Lecture Notes in Computer Science,2006(6):854-858.
[13]CHU S C,TSAI P W.Computational intelligence based on the behavior of cats[J].International Journal of Innovative Computing Information and Control Ijicic,2007,3(1):163-173.
[14]李淑梅,庄铭杰,庄弘.二进制描群算法在大规模MIMO天线选择中的应用[J].电讯技术,2017(6):698-702.
[15]马知也,施秋红.猫群算法研究综述[J].甘肃广播电视大学学报,2014(2):41-45.