A Quantum Ant Colony Multi-Objective Routing Algorithm in WSN and Its Application in a Manufacturing Environment
A Quantum Ant Colony Multi-Objective Routing Algorithm in WSN and Its Application in a Manufacturing Environment
复制标题
无线传感器网络中的量子蚁群多目标路由算法及其在制造环境中的应用
DOI：
10.3390/s19153334
复制
发表时间：
2019-08-01
期刊：
影响因子：
3.9
通讯作者：
Xu, Gaowei
中科院分区：
文献类型：
--
作者：
Li, Fei;Liu, Min;Xu, Gaowei
在许多复杂的制造环境中，运行中的设备必须通过无线传感器网络（wsn）进行监控，这不仅要求wsn具有较长的使用寿命，而且需要实现设备监控数据快速、高质量地传输到监控中心。传统的无线传感器网络路由算法，如基本蚁群路由（BABR），只需要一条最短路径，而BABR算法收敛速度慢，容易陷入局部最优，导致算法过早停滞。在WSN路由研究算法中引入量子计算和多目标适应度函数，提出了一种新的WSN路由算法——量子蚁群多目标路由（QACMOR）。具体来说，使用量子比特表示节点信息素，并旋转量子门来更新搜索路径的信息素。搜索路径中节点的能耗、传输时延、网络负载均衡程度等因素作为适应度函数，确定最优路径。仿真分析和实际制造环境验证了QACMOR的性能改进。
In many complex manufacturing environments, the running equipment must be monitored by Wireless Sensor Networks (WSNs), which not only requires WSNs to have long service lifetimes, but also to achieve rapid and high-quality transmission of equipment monitoring data to monitoring centers. Traditional routing algorithms in WSNs, such as Basic Ant-Based Routing (BABR) only require the single shortest path, and the BABR algorithm converges slowly, easily falling into a local optimum and leading to premature stagnation of the algorithm. A new WSN routing algorithm, named the Quantum Ant Colony Multi-Objective Routing (QACMOR) can be used for monitoring in such manufacturing environments by introducing quantum computation and a multi-objective fitness function into the routing research algorithm. Concretely, quantum bits are used to represent the node pheromone, and quantum gates are rotated to update the pheromone of the search path. The factors of energy consumption, transmission delay, and network load-balancing degree of the nodes in the search path act as fitness functions to determine the optimal path. Here, a simulation analysis and actual manufacturing environment verify the QACMOR’s improvement in performance.