With the increasing demand for video streaming applications, HTTP Adaptive Streaming (HAS) technology has become the dominant video delivery technique over the Internet. Current HAS solutions only consider either client- or server-side optimization, which causes many problems in achieving high-quality video, leading to sub-optimal users’ experience and network resource utilization. Recent studies have revealed that network-assisted HAS techniques, by providing a comprehensive view of the network, can lead to more significant gains in HAS system performance. In this paper, we leverage the capability of Software-Define Networking (SDN), Network Function Virtualization (NFV), and edge computing to introduce a CDN-Aware QoE Optimization in SDN-Assisted Adaptive Video Streaming framework called CSDN. We employ virtualized edge entities to collect various information items (e.g., user-, client, CDN- and network-level information) in a time-slotted method. These components then run an optimization model with a new server/segment selection approach in a time-slotted fashion to serve the clients’ requests by selecting optimal cache servers (in terms of fetch and transcoding times). In case of a cache miss, a client’s request is served (i) by an optimal replacement quality (only better quality levels with minimum deviation) from a cache server, (ii) by a quality transcoded from an optimal replacement quality at the edge, or (iii) by the originally requested quality level from the origin server. By means of comprehensive experiments conducted on a real-world large-scale testbed, we demonstrate that CSDN outperforms the state-of-the-art in terms of playback bitrate, the number of quality switches, the number of stalls, and bandwidth usage by at least 7.5%, 19%, 19%, and 63%, respectively.

1. CSDN: CDN-Aware QoE Optimization in SDN-Assisted
HTTP Adaptive Video Streaming
46th
IEEE LCN 2021
October 2021
reza.farahani@aau.at | https://athena.itec.aau.at/
Reza Farahani, Farzad Tashtarian, Hadi Amirpour, Christian Timmerer, Mohammad Ghanbari, Hermann Hellwagner

2. Agenda
● Introduction
● State of the art
● Motivating example
● Proposed solution
● Evaluation setup
● Experimental results
● Conclusion and Future work

3. Introduction
3

4. ● Video traffic has become the dominant traffic over the
Internet.
● It is expected to reach more than 82% of all Internet traffic in
2021 [1].
● HTTP adaptive streaming (HAS) has been considered as the
de-facto video delivery technology over the Internet.
Introduction- Video Streaming
4
[1] Cisco. Global - 2021 Forecast Highlights. https://www.cisco.com/c/dam/m/en_us/solutions/service-provider/vni-forecast-highlights/pdf/Global_2021_Forecast_Highlights.pddf

5. ● The adaptation process can be performed with different schemes:
○ Pure client-based:
■ The decision is based on the local parameters, e.g.,
● buffer status
● estimated available bandwidth
■ Insufficient information about the network
● It can lead to a suboptimal adaptation decision
○ Network-assisted:
■ The decision is performed via a centralized network component with a global view of
the entire network topology.
■ can be more beneficial for the users’ QoE
● Fundamental paradigms of modern networks, i.e., SDN, NFV, edge computing have been
used in modern network-assisted frameworks
Introduction- Network-assisted video streaming
5

6. ● The fundamental paradigm of modern networks to
address the limitations of conventional network architecture
like:
○ Complex Network Devices
○ Management Overhead
○ Limited Scalability
● The control plane (forwarding decision) is decoupled from
the data plane (acts on the forwarding decision)
○ Centralized Network Controller
○ Standard communication Interface (OpenFlow),
○ Programmable Open APIs
Introduction-Software-Defined Networking (SDN)
6

7. ● It is considered as a complementary technology to SDN
● NFV enables Virtual Network Functions (VNFs) to
○ run over an open hardware platform
○ Reduce OpEx, CapEx
○ Accelerate innovations
Introduction-Network Function Virtualization (NFV)
7
Router
Switch Load Balancer (LB)
Firewall
Virtualization Layer
VRouter VFirewall
VSwitch VLB
VNF VNF
VNF VNF

8. State of the art
8

9. 9
Farahani, R., Tashtarian, F., Erfanian, A., Timmerer, C., Ghanbari, M. and Hellwagner, H., 2021, October. ES-HAS: An Edge- and SDN-Assisted
Framework for HTTP Adaptive Video Streaming,” in ACM NOSSDAV, 2021.(pp. 50-57).
ES-HAS: An Edge- and SDN-Assisted Framework for
HTTP Adaptive Video Streaming

10. Motivating example
10

11. Pure client-based approach
11
● Cache miss The cache server must hold the requests Fetch the requested
segments from the origin server

12. Pure client- ES-HAS
12
● Demanded quality levels are available only on CS2
● CS1 with more available bandwidth could serve the requested segments with higher
quality levels
● The requested segments are unavailable in all cache servers, and the quality deviation is
unacceptable for the clients
1
2

13. Proposed solution
13

14. Proposed solution
14
● CSDN equips the ES-HAS VRP with the transcoding capability
● CSDN’s VRPs receive the network information, plus user preferences
● CSDN’s VRPs take into account:
○ fetch-based actions
○ transcoding-based actions
● Increases the computation costs of the system.
● The backhaul bandwidth consumption and users’ QoE (based on their preferences)
are significantly improved by the VRP possibly performing additional actions.

15. CSDN Architecture
15
● We leverage SDN, NFV, edge computing and propose our architecture in three layers

16. Time-slot Structure
16

17. Server/Segment selection policy
17
Our server/segment policy is :
1. When the requested quality level exist in the cache servers (Cache hit)
○ find the cache server with minimum serving time
● Original requested quality
● Transcoded quality
2. When the requested quality level is not available in any cache server (Cache miss)
○ Use replacement quality from a cache server with minimum fetch time
○ Transcode the original quality from better quality level at the edge
○ fetch the original requested quality from the origin server

18. Evaluation setup
18

19. We evaluate the performance of CSDN compared to ES-HAS, SABR and pure client-based
approaches on a large-scale cloud-based testbed.
○ 100 clients
○ Four cache servers
○ Five OpenFlow switches
○ An SDN controller
○ Four VRP servers
○ A video Dataset including:
■ ten video sequences (BBB with 150 segments)
■ 2, 4, 6 segments
■ five representations
○ Two ABR algorithms (Squad, and BOLA)
○ MongoDB for cache-map transaction
○ Different Network paths with various bandwidth
○ Bandwidth monitoring (Floodlight Restful API)
○ LRU cache replacement policy
Testbed
19

20. Experimental results
20

21. ● CSDN outperforms the state-of-the-art in terms of:
○ Playback bitrate 7.5%
○ The number of quality switches 19%
○ The number of stalls 19%
User’s QoE in different approaches:
21

22. Network utilization in different approaches:
22

23. 23
Conclusion and Future work

24. ● This paper leverages the SDN and NFV paradigms to propose the CSDN framework
providing network assistance for HTTP adaptive video streaming
● We equip ES-HAS VRPs that employs a novel server/segment selection policy
● We implement the proposed framework and its modules on a cloud-based large-scale
testbed consisting of 100 clients and conducts experiments in different scenarios
● CSDN outperforms state-of-the-art approach in terms of users’ QoE and the network
utilization
● Edge caching, extending proposed MILP model, and utilizing learning- ,
(meta)heuristic-based approach are possible future work directions.
Ongoing and Future Work
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25. Thank you for your attention
reza.farahani@aau.at | https://athena.itec.aau.at/
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