Enhancing Quality of Service in Software-Defined Networks

Transcription

1 ALMA MATER STUDIORUM - UNIVERSITY OF BOLOGNA Department of Computer Science and Engineering Master Degree in Computer Engineering Enhancing Quality of Service in Software-Defined Networks Supervisor: Professor Antonio Corradi Correlator: Professor Mario Gerla Correlator: Professor Eduardo Cerqueira Correlator: Doctor Luca Foschini

2 Outline 2 1. Introduction 2. Background 3. QoS-aware Model 4. Implementation 5. Results 6. Conclusion

3 Introduction (I) 3 Motivations Internet ossification phenomenon: while technology and innovation continue to evolve, our network infrastructure system has been maintained almost in the same shape for decades. Quality of Service (QoS) guarantees: the explosive growth of real time applications brings the network programmers to design network protocols that deliver certain QoS performance guarantees. Coexistence of differentiating services with different requirements in terms of bandwidth, packet loss, latency, and also various implementation technologies in campus networks and every day scenarios.

4 4 Introduction (II) Quality of Service APPLICATION DELAY PACKET LOSS JITTER BANDWIDTH VoIP 150 ms * 1% < 30 ms * kbps Interactive-Video 150 ms * 1% 30 ms * n.a. Streaming-Video 4-5 s * 5% n.a. n.a. * "one-way" value T. Szigeti and C. Hattingh, End-to-End QoS Network Design: Quality of Service in LANs, WANs, and VPNs (Networking Technology). Cisco Press, 2004.

5 Introduction (III) 5 Software-Defined Networking paradigm SDN together with OpenFlow allows to control the behavior of the network by decoupling the control logic and the physical layer.

6 Background (I.I) Classical Switch 6

7 Background (I.II) SDN Switch 7

8 Background (II) flow entry packet-in OpenFlow-enabled Switch 8

9 Our QoS Architecture 9

10 QoS aware Model 10 Multi-Commodity Flow and Constrained Shortest Path Objective Function: The cost minimization that depends on the cost computed with the delay and packet loss of the used links. Constraints: The flow balancing, that the total flow incoming into each vertex is equal to the total flow outgoing from the same vertex, with the exception of the source and the terminal.

11 QoS aware Model 11 Multi-Commodity Flow and Constrained Shortest Path Constraints: The arch capacity constraint imposes a limit on the available bandwidth of each link. The maximum acceptable value for the packet loss Pkmax and the delay Dkmax, imposes the limit for each service k. The variables domain guarantees that the decision variable is 0 or 1.

12 Implementation (I) 12 Scenario at UCLA campus Two different flows: medical data, e.g., file transfer general data, e.g., multimedia service Various paths with different characteristics related to the packet loss, delay, and available bandwidth. In case of network congestion, it is necessary to: Reconfigure the paths. Guarantee the route for some specific flows instead of other. [UCLA campus map]

13 Implementation (II) Hybrid Network Topology in Mininet 13

14 Implementation (III) Details 14

15 15 Results (I) Short and Permanent Congestion Time (s) Time (s)

16 16 Results (II) Triggering Time (s) The Watch Dog module triggers the changing of the path when the throughput is under the chosen threshold. We call these specific warnings: false-positive.

17 17 Results (III) QoS aware (i) Link congestion during the video streaming service. New path followed by the video streaming flow to avoid the link congestion. Time (s)

18 18 Results (III) QoS aware (ii) New link congestion streaming service. during the video Second new path followed by the video streaming flow to avoid the new link congestion. Time (s)

19 19 Results (IV) Multi-Commodity Flow with QoS Link congestion during both streaming and the file transfer. the video New path followed by the video streaming and file transfer flows to avoid the link congestion. Time (s)

20 20 Results (V) Mean Opinion Score (MOS) and Function Cost FUNCTION COST MOS QUALITY IMPAIRMENT < 40 5 Excellent No block at all Good No block or a sporadic very short block Fair A couple of short blocks (1-2 s) Poor Several blocks (2-4 seconds long) > 80 1 Bad A lot of blocks (> 10) with long duration (7-10 s)

21 21 Conclusion We develop a modular and extensible architecture to enhance the Quality of Service in a Software Defined Networks. We allow dynamic and fast path reconfiguration in case of network overloading taking into account the service requirements such as packet loss, delay, and available bandwidth. We map the results given by our mathematical model into a MOS scale in order to represent the client perception of the service. As Future Work: We plan to use our QoS architecture to manage a seamless vertical handover between different technologies such as Wi-Fi, WiMAX, and LTE. We think that our QoS Architecture can improve the resource management and the path reconfigurability in a very dynamic scenario such as the Vehicular Ad-Hoc Networks (VANETs)*. * I. Ku, Y. Lu, E. Cerqueira, R. Gomes, F. Ongaro, and M. Gerla, Towards Software-Defined VANET: Architectures and Services, Med-Hoc-Net 2014.

22