A New Framework for Network Flow Queuing Delay Prediction Based on Stream Computing

In the network, accurately predicting network flow queuing delay is important for congestion control, network bandwidth allocation, and network performance improvement. In order to improve QoS (quality of service) and predict fine-grained queuing delay in advance, A framework is proposed in this paper. We firstly perform real-time preprocessing on fine-grained data packet, which is acquired using In-band Network Telemetry (INT) technology, based on the Storm platform. Then we use Spark Streaming to perform online prediction based on LSTM short-term prediction model which is obtained by training off-line data on the Spark platform. The online prediction and off-line training technology framework proposed in this paper will provide effective information for congestion avoidance or dynamic routing planning in real time.

[1]  Zhao Jin-bao.  Short-Term Freeway Traffic Flow Prediction Based on Multiple Methods with Bayesian Network , 2011 .

[2]  Shaya Sheikh,et al.  Mobile ad hoc network proactive routing with delay prediction using neural network , 2010, Wirel. Networks.

[3]  Yantai Shu,et al.  Study on network traffic prediction techniques , 2005, Proceedings. 2005 International Conference on Wireless Communications, Networking and Mobile Computing, 2005..

[4]  Li Li,et al.  Using LSTM and GRU neural network methods for traffic flow prediction , 2016, 2016 31st Youth Academic Annual Conference of Chinese Association of Automation (YAC).

[5]  Naixue Xiong,et al.  Predictive control for vehicular sensor networks based on round-trip time-delay prediction , 2010, IET Commun..

[6]  Yuehui Chen,et al.  Small-time scale network traffic prediction based on flexible neural tree , 2012, Appl. Soft Comput..

[7]  Adrian Popescu,et al.  NetForecast: A Delay Prediction Scheme for Provider Controlled Networks , 2007, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

[8]  Arindrajit Pal,et al.  Delay Prediction in Mobile Ad Hoc Network using Artificial Neural Network , 2012 .

[9]  Sanjay Kumar,et al.  Prediction analysis of delay in transferring the packets in adhoc networks , 2016, 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom).

[10]  A. Afshar,et al.  An MLP neural network for time delay prediction in networked control systems , 2008, 2008 Chinese Control and Decision Conference.

[11]  Peter C. Y. Chen,et al.  LSTM network: a deep learning approach for short-term traffic forecast , 2017 .

[12]  Harshita Tuli,et al.  A Review on Delay Prediction Techniques in MANET , 2014 .

[13]  Guoqiang Peter Zhang,et al.  Neural network forecasting for seasonal and trend time series , 2005, Eur. J. Oper. Res..