Abstract

Today, the Software-defined Network, with its advantages such as greater reliability via automation, more efficient network management, cost-savings, and faster scalability, is increasingly being deployed in many network systems and network operators. The most common deployment architecture is a distributed system with the existence of many independent domains, each controlled by an SDN controller. One of the well-known applications in SDN is server selection and routing. However, deploying server and route selection in distributed and heterogeneous SDN networks faces two issues. First, the lack of global views of the whole system is because the inter-communication between SDN domains has not been standardized for the distributed and heterogeneous SDN network. To solve this issue, we use our previous work, an open East-West interface called SINA, to adaptively guarantee the network state consistency of the distributed SDN network with multiple domains. Secondly, selecting the path for packet transmission based only on the current network states of a local SDN domain is ineffective as it can bring over-utilization to several links and under-utilization to others. Predicting the link cost of the whole path from the source to the destination is necessary. Therefore, this paper proposes an LSTM-based link cost prediction for the server and route selection mechanism in a distributed and heterogeneous SDN network. The experimental results show that our proposal improves up to 15% of link utilization, reduces 10% of packet loss, and obtains the lowest servers’response time compared to benchmarks

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.