Measurement cost minimization for monitoring link latency in Software-defined networking

In the field of next-generation networking, software-defined networking (SDN) is on the verge of becoming popular. The main concept of SDN is that networks can be rendered programmable. Network monitoring is an essential technique that can be employed to obtain large amounts of information from a network; for example, information regarding throughput, delay, and packet loss. Tools such as sFlow and NetFlow can be employed to monitor traditional networks; however, network devices require the capability to support such protocols. Furthermore, traditional network monitoring methods usually engender considerable overhead on the network. Although SDN and OpenFlow enable more efficient network monitoring, employing OpenFlow to monitor the network still results in additional overheads to the controller and switches, which affect their performance. This example is considered a trade-off. This thesis proposes a method of network monitoring based on adaptive polling that employs several control messages in OpenFlow to monitor the network efficiently, thereby achieving a highly accurate result with minimal costs.