ID 原文 译文
20515 随着数据中心网络流量的迅速增长，如何提高数据中心网络性能和服务质量成为了研究热点。 With the rapid growth of Data Center Network (DCN) traffic, how to improve the performance and service quality of data center network become a research hotspot.
20516 然而现有的流量调度算法在网络负载加大时，一方面会导致网络带宽碎片化从而使得网络吞吐量降低，另一方面忽视了流量应用需求导致网络服务质量较差。 However, when the network load increases, the existing traffic scheduling algorithm on the one hand may cause bandwidth fragmentation results in the network throughput decrease, on the other hand, it neglects the traffic application requirements to lead to poorQoS.
20517 为此，该文提出一种面向带宽碎片最小化和QoS保障的动态流量调度算法， Therefore, a dynamic traffic scheduling algorithm for bandwidth fragmentation minimization and QoSguarantee is proposed.
20518 算法综合考虑了带宽敏感的大流、时延与丢包敏感的小流的不同需求， The algorithm takes into account the different requirements of the bandwidth-sensitivelarge flows, and delay sensitive and packet-loss sensitive small flows.
20519 首先根据待调度流的源地址和目的地址建立最短路径集， Firstly, the shortest path set is establishedaccording to the source address and destination address of the to-be-scheduled flow.
20520 其次从中筛选出满足待调度流的带宽需求的所有路径， Secondly, all the paths thatsatisfy the bandwidth requirement of the to-be-scheduled flow are selected.
20521 然后根据路径剩余带宽信息和小流应用需求情况为每条路径建立权重函数， Then, the weight function is established for each path according to the free bandwidth of the path and the application requirements of the small flow.
20522 最后根据权重函数值利用轮盘赌算法选择转发路径。 Finally, the forwarding path is selected based on the weight function value by roulette algorithm.
20523 实验仿真结果显示，与其它算法相比，所提算法降低了小流的丢包率和时延，同时在网络负载较大时提升了网络吞吐量。 The network simulation results show that when the network load increases, the proposed algorithm reduces the packet loss rate and delay of small flows, and improves the network throughput compared with other algorithms.
20524 针对具有结构性噪声干扰的稀疏信号处理问题，该文提出一种基于贝叶斯理论的感知矩阵优化设计方法。 To solve sparse signal processing problem with structural noise interference, a method of sensing matrix optimization design based on sparse Bayesian theory is proposed.