Cost-effective logging using SDN architecture
AbstractExisting networking systems are hardware-based and rely on inflexible architectures. In recent years, Software defined networks (SDNs) has emerged as a new paradigm for nextgeneration networks. SDNs are proposed to separate control plane and data forwarding plane in the traditional networks to reduce the increasing complexity of the network equipment. This separation enables a programmable and flexible hardware infrastructure via OpenFlow protocol and provides great opportunities in terms of reducing operating cost, simplifying network management tasks, gathering network statistics, and accelerating innovation. Logging is a structure that records the events of a system and the users in the system. With logging operations, the actions making by each device can be recorded. Especially in places where more than one person connects to the internet such as hotels, cafes, restaurants, student dorms and companies etc., it is necessary to monitor and take logs of the events. Already, by the Law No 5651, to combat certain crimes committed on the internet, it has become obligatory to take logs to institutions or people who provide collective internet services. In this paper, a logging and monitoring system has been designed and implemented. For logging and monitoring proceses, sFlow, OpenFlow, Floodlight, Open vSwitch, node.js, and MySQL technologies have been used. sFlow technology is used to monitor the networks. sFlow standard gives complete visibility into the use of networks enabling performance optimization, usage, and defense against threats. OpenFlow is a protocol used in SDN environments to enable the SDN controller to interact with the data forwarding plane of the network devices. Floodlight software is used by SDN controller for network operations. Open vSwitch software which enables to handle the traffic loads is installed at Raspberry Pi 3 hardware. The obtained results show that the proposed system can take the flowtable records, transfer the records to node.js via sFlow, and save the records to MySQL via node.js. Finally, the network traffic is successfully monitored and logged.