一种基于蝙蝠算法的NDN网络路径选择方法

A path selection method for NDN networks based on bat algorithm

针对命名数据网络(named data networking,NDN)路径选择过程中传输速度慢的问题,采用蝙蝠算法优化NDN网络的路径选择。为了证明蝙蝠算法在路径选择上的优势,将蝙蝠算法、遗传算法和粒子群算法进行对比,得出蝙蝠算法求得最优解的概率更高、收敛速度更快,为此提出了一种基于蝙蝠算法的NDN网络路径选择(bat algorithm-path selection in NDN,BA-PSNDN)方法。对传输过程中的节点进行实时更新并计算,通过迭代选出最优路径进行数据传输。使用ndnSIM2.7软件进行仿真,通过在兴趣包和数据包中加入自定义段,保存数据包传输过程中的信息并进行路径选择,仿真出最优路径后输出时延信息。结果表明,BA-PSNDN方法在减少网络传输时延方面更优。

In response to the slow transmission speed in the path selection process of Named Data Networking(NDN),the bat algorithm is adopted to optimize path selection of NDN networks.To demonstrate the advantages of the bat algo-rithm in path selection,it is compared with the genetic algorithm and the particle swarm optimization algorithm,and it was found that the bat algorithm has a higher probability of finding the optimal solution and converges faster.Therefore,a Bat Algorithm Path Selection in NDN(BA PSNDN)method based on the bat algorithm was proposed,which updated and calculated nodes in real-time during the transmission process,and selected the optimal path through iteration for data transmission.A simulation was performed using ndnSIM2.7 by adding custom domains to interest packets and data packets,saving information during packet transmission,making path selection,and outputting delay information after simulating the optimal path.The results indicate that the BA-PSNDN method is superior in reducing network transmis-sion delay.