| 摘要: |
| 在低压电力线通信网络组网过程中，节点间距离较远或信道环境较为恶劣的条件下，节点上电会形成多个网络短时共存现象，严重影响网络通信的可靠性，因此探讨基于带有冲突避免的载波侦听多路访问+时分多址(CSMA/CA+TDMA)混合协议的多网络快速融合方法。该方法可智能识别区域内存在多个网络，自主选取介质访问控制(MAC)地址最小的网络为多网络融合方向，解散MAC地址较大的网络，解决多网络不确定性融合问题。在此基础上，针对遗传算法在服务质量(QoS)参数约束下局部搜索能力差、难以得到按需路由最优解的问题，在非对称信道环境下提出基于改进遗传蚁群算法的路由热备份方法，该方法中源节点和目的节点不参与交叉、变异操作，有效避免了无效染色体的生成。采用最佳保留机制找到较优解，将较优解转换为蚁群算法的初始信息素，从而得到全局的路由最优解。仿真结果表明，相较于传统算法，所提方法更为有效。 |
| 关键词: 泛在电力物联网 低压电力线通信 网络融合 路由方法 改进遗传蚁群算法 |
| DOI：10.16081/j.epae.202109005 |
| 分类号:TM73 |
| 基金项目: |
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| Low-voltage PLC network routing method based on improved genetic ant colony algorithm |
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CUI Ying
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Zhuhai Power Supply Bureau of Guangdong Power Grid Co.,Ltd.,Zhuhai 519000, China
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| Abstract: |
| In the networking of low-voltage PLC(Power Line Communication) network, multiple networks coexist for a short time when nodes are energized under the condition that the distance between nodes is relatively far or the channel environment is relatively harsh, which severely affects the communication reliability. Aiming at this problem, the multi-network rapid fusion method based on CSMA/CA+TDMA(Carrier Sense Multiple Access with Collision Avoid+Time Division Multiple Access) hybrid protocol is explored. The proposed method can intelligently identify multiple networks in the area, select the network with the smallest MAC(Media Access Control) address as the multi-network fusion direction, dissolve the network with relatively big MAC address. It can solve the problem of multi-network uncertain fusion. On this basis, to solve the existing problems that the genetic algorithm has poor local search ability under the constraint of QoS(Quality of Service) parameters and is difficult to obtain the optimal solution of on-demand routing, a hot standby routing method based on improved genetic ant colony algorithm is proposed in asymmetric channel environment. Since the source nodes and destination nodes are not involved in crossover and mutation, the generation of invalid chromosomes can be effectively avoided. The optimal retention mechanism is used to find an approximate optimal solution, and then the approximate optimal solution is converted into the initial pheromone of ant colony algorithm to find the global optimal solution. The simulative results show that the proposed method is more effective than the traditional methods. |
| Key words: Ubiquitous Electric Internet of Things low-voltage power line communication network fusion routing method improved genetic ant colony algorithm |
