机坪感知场景下基于移动智能体的机会路由控制方法

针对机坪感知网络中存在的间歇性路由及弱连接问题,提出一种基于移动智能体(M-Agent)的机会路由控制方法。根据机坪保障运行特点,利用M-Agent连接非连通子域,完成对机坪感知数据流的分类模型设计,实现数据机会传输控制最优决策及负载均衡的数据汇集。在ONE环境中进行仿真,实验结果与经典Epidemic和Prophet算法相比,在节点数和缓存容量层面,消息投递率提高约8.07%-20.6%、网络开销降低约20.31%-48.79%,通信时延降低7.48%-12.31%,表明该路由控制方法在机坪感知网络中的可行性与有效性。

Opportunistic routing control method based on M-Agentin apron sensing scenario

To solve the problems of intermittent routing and weak connection in apron-aware networks, an opportunistic routing control method based on mobile agent (M-Agent) was proposed. According to the characteristics of the apron guarantee operation, M-Agent is used to connect the non-connected subdomains, and the classification model design of the apron-aware data flow is completed to achieve the optimal decision of data opportunity transmission control and load balancing data collection. In the ONE environment, the simulation results show that the main performances of the network, such as message delivery rate, the experimental results are compared with the classic Epidemic and Prophet algorithms. In terms of the number of nodes and cache capacity, the message delivery rate is increased by about 8.07% -20.6%, the network overhead is reduced by about 20.31% -48.79%, and the communication delay is Decreased by 7.48% -12.31%, indicating the feasibility and effectiveness of the routing control method in apron-aware networks.