Networking for big data has to be intelligent because it will adjust data transmission requirements adaptively during data splitting and merging. Software-defined networking (SDN) provides a workable and practical paradigm for designing more efficient and flexible networks. Matching strategy in the flow table of SDN switches is most crucial. In this paper, we use a classification approach to analyze the structure of packets based on the tuple-space lookup mechanism, and propose a matching model of the flow table in SDN switches by classifying packets based on a set of fields, which is called an F-OpenFlow. The experiment results show that the proposed F-OpenFlow effectively improves the utilization rate and matching efficiency of the flow table in SDN switches for networked big data.
@article{arxiv.1712.09158,
title = {Matching model of flow table for networked big data},
author = {Yiheng Su and Ting Peng and Xiaoxun Zhong and Lianming Zhang},
journal= {arXiv preprint arXiv:1712.09158},
year = {2020}
}