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机构地区:[1]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,重庆400065
出 处:《光电子.激光》2013年第8期1472-1476,共5页Journal of Optoelectronics·Laser
基 金:国家“973”重点基础研究发展规划项目基金(2012CB315803);国家自然科学基金(61275077,61071117);重庆市教委自然科学基金(KJ110527);重庆市科委自然科学基金(cstc2013jcyjA40052)资助项目
摘 要:将网络编码和光网络相结合可以有效解决光网络的带宽资源利用率等问题。然而,在光网络中进行编码操作,又将增加光网的光域运算开销、复杂度和缓存需求。为了减少光网络中网络编码的操作次数,本文提出一种基于图压缩的方法优化光网络拓扑结构,结合智能优化遗传算法(GA)实现组播最大速率的光组播最小编码节点,通过对光网络拓扑结构中的一类特殊潜在编码节点进行压缩处理,达到缩小算法搜索空间、排除大量非最优解的目的。仿真结果表明,通过本文图压缩优化后的光网络拓扑结构,可以使得现有的智能优化GA在求解光组播最小网络编码路由问题时效率更高,寻找到的解更优。Multicast routing greatly increases the bandwidth resources consumption of optical network. Network coding is the most effective way to increase bandwidth utilization and network throughput. Combining network coding with optical network can effectively solve the problem of optical network bandwidth utilization of resources. But network coding operation in the optical network must increase the optical field operation cost, complexity and buffer demand. In order to decrease the number of operations of network coding in optical network, graph-compression is proposed to optimize the optical network to- pology structure,and then comsined with the intelligent optimization genetic algorithm, the method of minimizing the number of optical multieast network coding nodes is proposed in this paper. By compress- ing the special potential coding nodes in the optical network,the proposed method can reduce the algo- rithm search size and eliminate the non-optimal solutions. The simulation analysis and results show that the proposed intelligent optimization genetic algorithm is more efficient in solving optical multicast minimum network coding routing problem through optimizing the optical network topology structure with graph-compression operation.
分 类 号:TN929.11[电子电信—通信与信息系统]
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