这篇文章学习构造的问题最佳分层与网络为异构的网络编码多点传送。基于分层的 source coding 的灵活性,一个全球有利的优化计划被建议,它最大化异构的水池节点的总数产量为分层与网络由决定层的最佳的位率编码多点传送。为了解决这个全球有利的优化计划,特别在大规模异构的网络,一个新问题特定的基因算法(GA ) 进一步被建议。它不仅高效地寻找层位率的最佳的分配,而且在整个进化进程保证候选人解决方案的有效性。模拟结果证明这个新基于 GA 的优化计划能高效地获得最佳或令人满意地在最佳附近的小点率为分层与网络编码多点传送,甚至在大规模异构的网络。
This article studies the problem of constructing optimal layered multicast with network coding for heterogeneous networks. Based on the flexibility of layered source coding, a global-favorable optimization scheme is proposed, which maximizes the aggregate throughput of heterogeneous sink nodes for layered multicast with network coding by determining the optimal bit rates of the layers. To solve this global-favorable optimization scheme, especially in the large-scale heterogeneous networks, a new problem-specific genetic algorithm (GA) is further proposed. It not only searches efficiently for the optimal allocation of layer bit rates, but also guarantees the validity of candidate solutions that this new GA-based optimization scheme could obtain layered multicast with network coding, even in the large-scale in the whole evolutionary process. Simulation results demonstrate efficiently the optimal or satisfactorily near-optimal bit rates for heterogeneous networks.