改进的遗传模拟退火算法优化光组播网络编码

发布时间：2018-11-13 08:44

【摘要】：网络编码可以提高WDM光网络有限数目波长转换器的利用率,但是网络编码操作将增加光域运算开销、复杂度和缓存需求。为了达到光组播容量条件下尽可能减少网络编码的次数,结合遗传算法和基于模拟退火的个体接受策略,提出一种改进的遗传模拟退火算法(GSAA)。算法通过设计一个既能满足最大组播吞吐量又考虑波长连续性约束路由的算法适应度函数实现网络编码次数减少;为保证种群空间中部分染色体可行性,算法在初始种群中加入一部分可行人工染色体;为了提高算法的局部搜索能力和收敛速度,算法在迭代过程中设计了一个局部搜索过程和自适应变异操作。仿真结果表明:改进的GSAA在收敛速度、网络编码次数等方面优于其它遗传算法。
[Abstract]:Network coding can improve the utilization of the limited number of wavelength converters in WDM optical networks, but the network coding operation will increase the overhead, complexity and cache requirements of optical domain. In order to reduce the number of network coding under the condition of optical multicast capacity, an improved genetic simulated annealing (GSAA).) algorithm is proposed by combining genetic algorithm and simulated annealing based individual acceptance strategy. The algorithm can reduce the number of network coding by designing an algorithm fitness function which can satisfy the maximum multicast throughput and consider the wavelength continuity constraint routing. In order to ensure the feasibility of some chromosomes in the population space, the algorithm adds some feasible artificial chromosomes to the initial population. In order to improve the local search ability and convergence speed of the algorithm, a local search process and an adaptive mutation operation are designed in the iterative process. Simulation results show that the improved GSAA is superior to other genetic algorithms in convergence speed, network coding times and so on.
【作者单位】：重庆邮电大学通信与信息工程学院重庆市光纤通信技术重点实验室;
【基金】：国家自然科学基金(61275077,61071117,51175535) 重庆市科委自然科学基金(CSTC,2013BB2425,2012jjB40009)资助项目
【分类号】：TN929.1

【参考文献】