LearnQoS: a learning approach for optimizing QoS over multimedia-based SDNs
| Autor: | Orhan Gemikonakli, Ramona Trestian, Ahmed Al-Jawad, Purav Shah |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
Multimedia
Computer science business.industry Quality of service 05 social sciences 050801 communication & media studies 020206 networking & telecommunications Provisioning 02 engineering and technology computer.software_genre Backhaul (telecommunications) Network management 0508 media and communications Qos management Packet loss 0202 electrical engineering electronic engineering information engineering Reinforcement learning business Software-defined networking computer |
| Zdroj: | BMSB |
| ISSN: | 2155-5052 |
| Popis: | As video-based services become an integral part of the end-users' lives, there is an imminent need for increase in the backhaul capacity and resource management efficiency to enable a highly enhanced multimedia experience to the end-users. The next-generation networking paradigm offers wide advantages over the traditional networks through simplifying the management layer, especially with the adoption of Software Defined Networks (SDN). However, enabling Quality of Service (QoS) provisioning still remains a challenge that needs to be optimized especially for multimedia-based applications. In this paper, we propose LearnQoS, an intelligent QoS management framework for multimedia-based SDNs. LearnQoS employs a policy-based network management (PBNM) to ensure the compliance of QoS requirements and optimizes the operation of PBNM through Reinforcement Learning (RL). The proposed LearnQoS framework is implemented and evaluated under an experimental setup environment and compared with the default SDN operation in terms of PSNR, MOS, throughput and packet loss. |
| Databáze: | OpenAIRE |
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