摘要
提出一种新型自适应遗传算法并与DTN(Delay Tolerant Networks)融合,解决DTN网络路由拥塞问题。该方法首先在奖罚策略基础上使用一个关于时间t的函数,代替传统算法的常数Q,完成对信息素的自适应动态更新,加快路径寻优速度,强化较优解;其次,将改进算法应用于DTN网络阻塞,对源节点至目的节点信息进行多次传输并赋予各节点信息素和启发值,实现节点中转价值和设计中转评价参数,达到动态选取中转节点效果,降低网络阻塞可能性。仿真结果表明,算法在执行效率和网络阻塞率方面得以改进与提升,整体性能优于相关算法。
A new adaptive genetic algorithm is proposed and integrated with DTN(Delay Tolerant Networks)to solve the rout⁃ing congestion problem of DTN network.Firstly,based on the reward and punishment strategy,this method uses a function about time t to replace the constant Q of the traditional algorithm to complete the adaptive dynamic update of pheromone,speed up the path optimization speed and strengthen the better solution.Secondly,the improved algorithm is applied to DTN network blocking,the information from the source node to the destination node is transmitted for many times,and the pheromone and heuristic value of each node are given to realize the node transfer value and design the transfer evaluation parameters,so as to achieve the effect of dy⁃namically selecting the transfer node and reduce the possibility of network blocking.Simulation results show that the algorithm can improve the execution efficiency and network blocking rate,and the overall performance is better than the related algorithms.
作者
王云
李丛
WANG Yun;LI Cong(Taizhou College of Science and Technology,Nanjing University of Science and Technology,Taizhou 225300)
出处
《计算机与数字工程》
2025年第1期127-132,共6页
Computer & Digital Engineering
基金
国家自然科学基金项目(编号:61871430)资助。
