基于逻辑分区的仿箱鲀鱼群负载均衡分簇控制算法

为实现水下仿箱鲀鱼群体协同控制, 并降低网络节点间负载的不均衡性导致的能量损 耗, 提升群体续航能力, 提出一种基于逻辑分区的负载均衡分簇控制算法. 首先实现局部快速分簇, 减少节点间维护报文数量, 降低系统整体开销； 然后基于 簇内逻辑分区策略, 实现监测、 保障和侦察多区域协同控制, 并结合最小响应时间整编零散鱼群, 优化网络控制体系的同时提高组网灵活性； 最后在维护过程中采用区域节点角色转换机制, 实现网络负载均衡. 通过仿真分簇实验验证了算法的有效性, 并结合网络能量消耗、 网络生命周期和能量均衡性3个指标验证算法的可行性.

Load Balancing Clustering Control Algorithm of Imitation Box Fish Based on Logical Partition

In order to realize cooperative control of underwater imitation box fish group, reduce the energy loss caused by the load imbalance among the network nodes, and improve the group endurance, we proposed a load balancing clustering control algorithm based on logical partition. Firstly, local fast clustering was realized to reduce the number of maintenance messages between nodes and the overall cost of the system. Secondly, based on the logical partition strategy within the cluster, it realized multi-regional cooperative control of monitoring, support and reconnaissance, integrated scattered fish schools with minimum response time, optimized the network control system and improved the flexibility of networking. Finally, in the process of maintenance,  the role transformation mechanism of regional nodes was used to realize the network load balance. The effectiveness of the algorithm was verified by simulation clustering experiments, and the feasibility of the algorithm was verified by combining the three indicators of network energy consumption, network life cycle and energy balance.