## 6 Conclusions  
This study explains the issues that can arise when SDN is configured with switches of very different sizes of the flow tables and proposes the SFF scheme to resolve them. The SFF scheme classifies the flow into short and long flows by using matching periods of the flow. It replaces the short flow first and keeps the long flow as long as possible. The long flow may send packets for a longer time than the short flow so that it reduces the total number of changing flow entries. Therefore, the SFF scheme also reduce the overheads of the switch and message exchange. According to our experiments with diverse switch conditions, the proposed SFF scheme shows the best performance in comparison with the other FIFO, LFU and LRU schemes.  
The proposed scheme divides the flows into the short flows and long flows. Then, it attempts to delete the entry among short flows first. To do this, the proposed scheme searches the flow table twice in the worst case. In addition, it requires a change of the logic of the switch that may be a little more difficult than that of the controller. However, the change of the controller will cause an increase of the processing overhead of the controller and the message exchange overhead using OpenFlow protocol between the switch and the controller.  
It is believed that many studies should be conducted to reduce the packet processing time and improve the switch memory efficiency in the future. Moreover, studies have to be carried out focusing on a technique that allows choosing an efficient scheme that fits a situation with more diverse traffic patterns, as well as real Internet traffic. Additionally, the studies and performance comparisons need to be performed under the actual networks such as datacenter, enterprise and contents delivery networks. Lastly, studies have to be combined and optimized with diverse hardware aspects such as TCAM, Application-Specific Integrated Circuit (ASIC), millions of flow entries capacity and gigabits per second port speed. This is because the final performance of a system is the performance of the final system implemented. In this paper, we showed the performance of flow entry replacement algorithms at the  
Figure 12: Experiment results with 160-128-96 flow table size.  
Figure 13: Experiment results with 96-128-160 flow table size.  
algorithmic level. Our algorithm showed a good performance with diverse aspects. However, it is not the final performance. It can be combined with TCAM at the implementation level and we need to consider the latency of the TCAM which occurs when we access, insert and delete a flow entry in the TCAM in the future. In addition, we have to make a mathematical model to support the proposition that the innovation can be scaled up to real and high performance physical switches.  
Conceptualization, N.K. and B.-D.L.; methodology, N.K.; software, Y.J.; validation, Y.J. and C.L.; writing--original draft preparation, D.K.; writing--review and editing, N.K. and C.L.; supervision, B.-D.L.; project administration, B.-D.L.; funding acquisition, N.K. All authors have read and agreed to the published version of the manuscript.  
This work was supported by Kyonggi University's Graduate Research Assistantship 2020. This work was also supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2017R1D1A1B04027874).  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.