• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Kalman Filtering-based Traffic Prediction for Software Defined Intra-data Center Networks


Abstract

Global data center IP traffic is expected to reach 20.6 zettabytes (ZB) by the end of 2021. Intra-data center networks (Intra-DCN) will account for 71.5% of the data center traffic flow and will be the largest portion of the traffic. The understanding of traffic distribution in Intra-DCN is still sketchy. It causes significant amount of bandwidth to go unutilized, and creates avoidable choke points. Conventional transport protocols such as Optical Packet Switching (OPS) and Optical Burst Switching (OBS) allow a one-sided view of the traffic flow in the network. This therefore causes disjointed and uncoordinated decision-making at each node. For effective resource planning, there is the need to consider joining the distributed with centralized management which anticipates the system’s needs and regulates the entire network. Methods derived from Kalman filters have proved effective in planning road networks. Considering the network available bandwidth as data transport highways, we propose an intelligent enhanced SDN concept applied to OBS architecture. A management plane (MP) is added to conventional control (CP) and data planes (DP). The MP assembles the traffic spatio-temporal parameters from ingress nodes, uses Kalman filtering prediction-based algorithm to estimate traffic demand. Prior to packets arrival at edges nodes, it regularly forwards updates of resources allocation to CPs. Simulations were done on a hybrid scheme (1+1) and on the centralized OBS. The results demonstrated that the proposition decreases the packet loss ratio. It also improves network latency and throughput—up to 84 and 51%, respectively, versus the traditional scheme.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
J. Mbous, T. Jiang, M. Tang, S. Fu and D. Liu, "Kalman Filtering-based Traffic Prediction for Software Defined Intra-data Center Networks," KSII Transactions on Internet and Information Systems, vol. 13, no. 6, pp. 2964-2985, 2019. DOI: 10.3837/tiis.2019.06.011.

[ACM Style]
Jacques Mbous, Tao Jiang, Ming Tang, Songnian Fu, and Deming Liu. 2019. Kalman Filtering-based Traffic Prediction for Software Defined Intra-data Center Networks. KSII Transactions on Internet and Information Systems, 13, 6, (2019), 2964-2985. DOI: 10.3837/tiis.2019.06.011.