Detection of Delivery Servers in Online Video Service using Long Short Term Memory Network

Wenyao Zheng, Jun Liu, Wenhui Lin

Abstract


Nowadays large scale video delivery networks have been widely deployed. Information about video delivery servers is crucial for a series of network management tasks. However, it is a challenge to identify the delivery servers in the ever-changing content delivery networks. Moreover, it is difficult to find general and flexible features to identify video delivery servers from various video service providers. In this paper, we mainly come up with a novel method based on LSTM (Long Short Term Memory Network) to detect video delivery servers. Experimental results prove that our approach works pretty well by comparing it with the other two conventional machine learning methods. What’s more, our approach can work more flexibly without cumbersome feature extraction relative to conventional machine learning methods.


DOI
10.12783/dtcse/csae2017/17524

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