CAJ | 학술논문

时延矩阵的重建是延迟敏感型应用优化的重要基础。在深入探讨分布式网络环境下一类基于矩阵分解的非梯度下降重建算法鲁棒性的基础上，分析了时延序列抖动对算法中的不适定与病态问题反演求解的强烈影响。为了降低这种影响，在引入正则化项改善系数矩阵谱特征的基础上，提出了一种时延序列的中值-卡尔曼时空联合滤波框架以抑制抖动污染，并通过统计特征的提取实现了拓扑突变感知，从而提高动态环境下的时延矩阵重建的性能。实验结果表明，滤波重建算法可在保留时延序列主要统计特征的基础上有效避免时延噪声造成的性能损失，并提供平稳的时延估计服务，始终将应力系数保持在较低的水平上。
시연구진적중건시연지민감형응용우화적중요기출。재심입탐토분포식망락배경하일류기우구진분해적비제도하강중건산법로봉성적기출상，분석료시연서렬두동대산법중적불괄정여병태문제반연구해적강렬영향。위료강저저충영향，재인입정칙화항개선계수구진보특정적기출상，제출료일충시연서렬적중치-잡이만시공연합려파광가이억제두동오염，병통과통계특정적제취실현료탁복돌변감지，종이제고동태배경하적시연구진중건적성능。실험결과표명，려파중건산법가재보류시연서렬주요통계특정적기출상유효피면시연조성조성적성능손실，병제공평은적시연고계복무，시종장응력계수보지재교저적수평상。
Latency matrix completion is an important foundation of latency-sensitive applications optimization. On the basis of the in-depth discussion of the robustness of a kind of matrix-factorization based non-gradient descending completion methods, this paper analyzes the significant impact to the intrinsic ill-posed and ill-conditioned inverse problems in the methods caused by the oscillations of the latency sequences. To mitigate the impact and improve the performance of the matrix completion methods in the wild, a regularization factor is introduced to improve the spectrum signature of the coefficient matrix, a median-Kalman filter, a time-spatial federated filtering scheme, is proposed to smooth the latency sequences, and then the topology mutation is obtained through extracting the statistic characters of the latency sequences. The experiments show that our method can avoid the performance degradation caused by noises without losing the major characteristics of the latency sequences, provide robust latency estimation capability, and keep the stress coefficient at a low level about 0.13 during the whole life cycle of the network.