CAJ | 학술논문

本文针对多路径并行传输提出了一种基于自学习思想的路径选择算法。这种自学习机制首先根据具体服务提出的需求，如吞吐量、延时、丢包等，综合定义一个用于计算服务体验的目标函数，再将路径选择算法中的一些参数设定为可学参数。在传输过程中，系统通过分析不同可学习参数与目标函数值之间的对应变化关系，逐渐进行自我学习，得到最佳的可学参数配置，从而获得最优化的服务体验。实验测试结果表明了自学习选路算法的可行性、收敛性和稳定性，并且证明了该算法能够根据网络状态的实时变化，通过自学习机制自行调整路径分配并得到最佳的目标函数值。
본문침대다로경병행전수제출료일충기우자학습사상적로경선택산법。저충자학습궤제수선근거구체복무제출적수구，여탄토량、연시、주포등，종합정의일개용우계산복무체험적목표함수，재장로경선택산법중적일사삼수설정위가학삼수。재전수과정중，계통통과분석불동가학습삼수여목표함수치지간적대응변화관계，축점진행자아학습，득도최가적가학삼수배치，종이획득최우화적복무체험。실험측시결과표명료자학습선로산법적가행성、수렴성화은정성，병차증명료해산법능구근거망락상태적실시변화，통과자학습궤제자행조정로경분배병득도최가적목표함수치。
In this paper ,we propose a path selection scheme based on the idea of autonomous learning for concurrent multi-path transfer (CMT ) in path selection .Firstly ,this autonomous learning scheme integrates the requirements of a specific service , such as throughput ,delay and loss rate ,to define the optimization object function .Secondly ,this scheme sets several parameters of path selection as the learning parameters .During the transmission ,through analyzing the relationship between different values of learning parameters and the actual measured values of object function ,the system performs its autonomous learning ,and gradually gets the best value combination of learning parameters .Experimentations show the feasibility ,convergence and stability of the scheme ,and also demonstrate the scheme could adjust the learning parameters by itself to adapt the changing network condition and gain the best value of object function .