# An Efficient Network Resource Management in SDN for Cloud Services
## 3 Need for Network Resource Management in SDN  
In a cloud-based service, a flow can be created and removed when a service begins and ends, respectively. Each flow takes a different form depending on the transmission pattern of the packets, and this pattern can vary depending on the type of service requested and the state of the service. Figure 1 shows an example of the internal packet sequence of the flow developed when two services are created. As indicated in the figure, the number of packets entering the flow varies dynamically depending on the state of each service. For example, regarding the flow for processing a real-time streaming service, the packets consistently come in at regular time intervals. In the flow for processing a web service, the packets explosively come in only when the web moves or starts, after which the packets occasionally enter to maintain the session. Therefore, the packet pattern of each flow differs owing to various factors when multiple users request multiple services. This difference dynamically changes the amount of network resources used by the flow. Figure 1: Example of difference in traffic pattern of flow based on service. A cloud system can use the network resources of various paths to deliver the desired content to the user. If highly effective network resources with low cost are first allocated to a flow that consumes a large amount of network resources, the user QoE can be significantly improved. Figure 2 shows an example of a cloud network topology with two different network cost paths and three service flows with a dynamically changing the amount of data transmitted. The cloud system shown in Figure 2a has two different paths between the user and server. It is assumed that the s1-s3-s5 path is less costly than the s1-s2-s4-s5 path and can support only a single service flow. Figure 2b shows the size of the data transmission required when processing the three services. In this scenario, if the cloud network is configured using a traditional network structure, the network resources cannot be dynamically allocated according to the amount of data. Therefore, in the traditional network structure, when Service1 is first requested, it is transmitted through the s1-s3-s5 path and the remaining services are transmitted through the s1-s2-s4-s5 path. At this time, when the network utilization is analyzed over time, Service1 is considered to effectively transmit most of the data in the t\({}_{0}\)-t\({}_{1}\) section, thus using the path efficiently. However, in the t\({}_{1}\)-t\({}_{2}\) section, Service2 is transmitting most of the data but cannot use the low cost path. In the t\({}_{2}\)-t\({}_{3}\) section, Service1 transmits hardly any data, whereas Service3 steadily transmits data, leading to a sharp decrease in network utilization. Consequently, in a traditional network structure, network resources cannot be efficiently used because they cannot be dynamically allocated according to the amount of data transmitted. If the traffic pattern changes are detected in real time and paths are dynamically allocated using the SDN structure, network resources can be more efficiently managed. The SDN structure enables the changes in the amount of data transmitted by each service flow to be identified in real time. Thus, it can dynamically allocate the most efficient network resources to the service flow that transmits the most data per unit time according to the amount of data transmission identified. If the SDN structure is adopted in the above example, the s1-s3-s5 network path can be switched and allocated to Service1, Service2, Service3, Service1, and Service3 per unit time. In this manner, the network efficiency continues to increase, thereby increasing the user's QoE. However, we should accurately predict the changes in flow arising from various factors to obtain such results. Therefore, in this study, we propose a method for more precisely detecting and processing the flow changes in an SDN structure.