QL-CSFQ:一种结合队列长度的CSFQ算法

当存在适应流时,网络流量的测量值与实际值存在比较大的误差,这将严重影响CSFQ算法中公平共享速率α值的计算准确性,从而大大降低网络流之间的公平性.针对这一问题,本文提出了一种结合队列长度的CSFQ算法—QL-CSFQ.在QL-CSFQ算法中,采用结合队列长度状态信息来提高公平共享速率α值的计算准确性,从而有效提高了存在适应流情况下的网络流之间的公平性.大量模拟实验结果表明在存在适应流情况下QL-CSFQ有效消除了测量误差对算法公平性的影响,提高了网络流之间的公平性.

QL-CSFQ:A Queue Length Embedded Core-Stateless Fair Queue Algorithm

In CSFQ,when there exist adaptive flows there will be error between the measurement value of throughput and its real value,furthermore the fairness is seriously degraded.To resolve the problem,the paper mainly studies that how to improve the accuracy of the computation of α value,and proposes a queue length embedded core-stateless fair queue algorithm (QL-CSFQ).In QL-CSFQ,the queue length is concerned to improve the accuracy of the computation of α value.The paper compares QL-CSFQ to CSFQ in fairness,utilization of bandwidth,the queue length and its jitter using large amount of simulations,and the results show that QL-CSFQ can decrease the impact of measurement error on the fairness.