【摘要】 针对RapidIO网络QoS路由选择问题,提出一种基于改进萤火虫算法的RapidIO路由选择策略。首先,利用高斯变异和存储机制对传统萤火虫算法进行优化,高斯变异可以有效控制算法搜索空间中解的散射程度,使算法避免陷入局部最优,存储机制有利于评估并存储每只萤火虫的历史状态,防止信息丢失。然后,将改进后的萤火虫算法与实际RapidIO网络QoS问题相结合,选择出最终的最佳路由策略。实验结果表明,在所模拟的RapidIO测试网络中,改进后的萤火虫算法时延为42 ms,时延抖动为8 ms,代价最低为64 ms,共需要迭代的次数为8,相较于其他算法曲线更加稳定,更能快速找到最优解,表现出的性能最优,有效解决了RapidIO网络QoS路由选择问题。更多还原

【Abstract】 Aiming at the problem of QoS routing in RapidIO network, a RapidIO routing strategy based on improved glowworm swarm optimization algorithm was proposed. Firstly, gaussian mutation and storage mechanism were used to optimize the traditional firefly algorithm. Gaussian mutation can effectively control the scattering degree of the solution in the search space of the algorithm, so that the algorithm avoids falling into a local optimum. The storage mechanism is conducive to evaluating and storing the historical state of each glowworm, preventing information loss. Then combine the improved glowworm swarm optimization algorithm with the actual RapidIO network QoS problem and select the final best routing strategy. The experimental results show that in the simulated RapidIO test network, the improved glowworm swarm optimization algorithm has a delay of 42 ms, delayed jitter of 8 ms, a minimum cost of 64 ms, and a total of 8 iterations, which is more stable than other algorithm curves. It can find the optimal solution more quickly and show the best performance, effectively solving the QoS routing problem of RapidIO network.更多还原