基于自回归模型的网络数据去重算法的设计

为了提高网络带宽利用率，实现网络负载和传输效率的平衡，提出了一种基于网络流量自回归技术的网络数据去重算法ANTREA. 该算法将数据传输分割成多个传输单元，在每个传输单元中分成去重传输和直接传输2部分，前一部分实现去除冗余数据后传输，后一部分数据则利用空闲带宽实现传输. 通过为每个传输单元的网络状况建模，预测下一个传输单元的网络可用带宽及查重处理时间，并据此调整直接传输的数据量，以求充分利用空闲带宽，提高网络带宽利用率. 实验结果表明，ANTREA算法可以根据网络状况自动调整传输策略，能够充分利用网络带宽以实现更高的数据传输效率，比EndRE算法有更好的网络适应性，在10 MB/s的网络环境下，传输吞吐量几乎为EndRE的7倍.

Design of Autoregressive-Based Network Traffic Redundancy Elimination Algorithm

For purpose of enhancing network bandwidth utilization and for a balance between network traffic and transfer efficiency, based on the network traffic autoregressive technology, a new network traffic redundancy elimination algorithm called ANTREA was proposed. It splits data transfer missions into transfer units. The data in one transfer unit are executed in two ways, one is traditional traffic redundancy elimination, and the other is direct data transfer. A transfer unit makes up models of network situation, and predicts the time cost of checking duplications and the available bandwidth. So, it adjusts the size of direct data transfer according to the result of prediction. Experiments show that ANTREA algorithm can adjust its transfer strategy according to the network situation and utilize network bandwidth sufficiently to achieve higher transfer efficiency. It is of better flexibility on network situation than EndRE and has almost 7 times transfer throughput than EndRE in network with 10MB/s bandwidth.