One method from LRD to SRD

Authors:
Bo Gao;Qin-yu Zhang;Yong-sheng Liang;Nai-tong Zhang
Affiliations:
Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China and Institute of Information Technology, Shenzhen Institute of Information Technology, Shenzhen, China;Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China;Institute of Information Technology, Shenzhen Institute of Information Technology, Shenzhen, China;Shenzhen Graduate School, Harbin Institute of Technology, Shenzhen, China
Venue:
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
Year:
2009

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Abstract

Research of self-similarity has been the focus of flow prediction due to the complexity of self-similar traffic, but the LRD (long range dependence) traffic has the disadvantages of the high modeling algorithm complexity and poor precision. Therefore we tried to propose a way that can make the LRD traffic change to SRD (short range dependence) which is more simple than LRD in the field of modeling and predicting. The researchers adopted EMD (Empirical Mode Decomposition) to decompose LRD data which would be decomposed into several IMF (Intrinsic Mode Function) components. Then we found that IMF components had no longer self-similar property through theoretical analysis and simulation, thus people could use some SRD model to forecast traffic.