Chunk-level request-grant-transfer mode for QoE-sensitive video delivery in CDN

Remote Direct Memory Access (RDMA) can be deployed in Content Delivery Networks (CDN) Points of Presence (PoPs) to avoid the high CPU overheads caused by traditional TCP/IP stacks. However, RDMA cannot surmount the drawbacks of the window-based conservative of TCP and is insensitive to Quality of Ex...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Proceedings of the International Symposium on Quality of Service s. 1 - 10
Hlavní autoři: Shen, Gengbiao, Li, Qing, Jiang, Yong, Sinnott, Richard, Lin, Dong, Guo, Zehua, Wang, Yi
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: New York, NY, USA ACM 24.06.2019
Edice:ACM Other Conferences
Témata:
ISBN:9781450367783, 145036778X
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Remote Direct Memory Access (RDMA) can be deployed in Content Delivery Networks (CDN) Points of Presence (PoPs) to avoid the high CPU overheads caused by traditional TCP/IP stacks. However, RDMA cannot surmount the drawbacks of the window-based conservative of TCP and is insensitive to Quality of Experience (QoE). Moreover, the requirement of lossless networks hinders the widespread application of RDMA. In this paper, we introduce the parallel multipoint-to-multipoint Request-Grant-Transfer (RGT) mode into RDMA to solve the aforementioned problems. Compared with traditional RGT mode, our scheme supports parallel Dynamic Adaptive Streaming over HTTP (DASH) chunk delivery, thereby improving throughput and reducing initial delays. We differentiate the importance of DASH chunks according to QoE-related properties. In this way, we reduce the response time of specific DASH chunks. We provide an efficient approach to select the optimal number of requests for partially traversing pending requests to reduce the overheads of Request stages. We perform comprehensive experiments to demonstrate that our scheme improves the throughput of CDN PoPs and enhances client QoE.
ISBN:9781450367783
145036778X
DOI:10.1145/3326285.3329047