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A Link delay computation method for the quality of service support in software defined networks

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2019
Balo, Efe
Packet switched networks cannot provide tight delay bounds that are required by certain types of applications despite facilitating high throughput. Therefore, delay measurementtechniquesforpacket-switchednetworkshavealwaysgrabbedtheattention of the community to both utilize advantages of packet-switched networks and provide a realistic end to end delay prediction of packets. Software Defined Networking (SDN) isa new paradigmofpacket-switchednetworkingwhichgathersmanagement functionality of network in a logically single controller. SDN is thought to eliminate problems of legacy layered architecture by utilizing the control information coming from all network layers. However, in SDN topology, control plane and data plane are separated which implies control packets for network management flow in a different channel than datapath channel. Moreover, the SDN controller has to have a decision metric similar to legacy link-state computation approaches in order to calculate the most efficient route in the topology. All of these indicate that link delay computation in SDN needs new perspectives different than the legacy network to achieve its proper operation. In this thesis, we propose a link delay computation method for SDN topologies. For this purpose, we construct a framework which uses standard OpenFlow messages and computes the switch queuing delay in run-time. In this framework, we model each queue in SDN switches as a G/G/1 queue and measure the ingress traffic with OpenFlow meters. Then, we utilize meter statistics to obtain mean and variance of interarrival times between packets. After finding the average state of the queues we eventually infer the respective queuing delay from Little’s equation. We demonstrate our method in three cases which are single flow per queue, multiple flows per queue and a test application which uses our delay information to determine the fastest queue of an SDN switch port. Also, we discuss the accuracy and the application limitations of the proposed method.