Minimizing Server Throughput for Low-Delay Live Streaming in Content Delivery Networks. F. Zhou, S. Ahmad, E. Buyukkaya, R. Hamzaoui and G.
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1 Minimizing Server Throughput for Low-Delay Live Streaming in Content Delivery Networks F. Zhou, S. Ahmad, E. Buyukkaya, R. Hamzaoui and G. Simon
2 Live Stream Delivery Content Provider CDN encoders ingest server origin server edge servers Clients 2 / 13 Gwendal Simon Minimizing Server Throughput in CDN
3 Live Stream Delivery Content Provider CDN encoders ingest server origin server edge servers Clients Recent large-scale live video streaming failed Superbowl Korean Telecom and smart TVs 2 / 13 Gwendal Simon Minimizing Server Throughput in CDN
4 Motivations Where is the bottleneck in today s CDN? ISP 1 ISP 2 ISP 3 origin servers reflectors edge servers 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
5 Motivations Where is the bottleneck in today s CDN? ISP 1 ISP 2 ISP 3 origin servers reflectors edge servers last-mile? 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
6 Motivations Where is the bottleneck in today s CDN? ISP 1 ISP 2 ISP 3 origin servers reflectors edge servers last-mile? adaptive streaming last-mile 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
7 Motivations Where is the bottleneck in today s CDN? origin servers reflectors edge servers peering link? ISP 1 ISP 2 ISP 3 adaptive streaming last-mile 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
8 Motivations Where is the bottleneck in today s CDN? origin servers reflectors edge servers peering link? ISP 1 ISP 2 ISP 3 adaptive streaming last-mile edge servers in ISP peering link 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
9 Motivations Where is the bottleneck in today s CDN? ISP 1 ISP 2 ISP 3 origin servers reflectors edge servers infrastructure? adaptive streaming last-mile edge servers in ISP peering link 3 / 13 Gwendal Simon Minimizing Server Throughput in CDN
10 The upload capacity equipment bottleneck 6 CPU 2 NIC / 13 Gwendal Simon Minimizing Server Throughput in CDN
11 The upload capacity equipment bottleneck 6 CPU 2 2 NIC / 13 Gwendal Simon Minimizing Server Throughput in CDN
12 Our proposal no cooperation
13 Our proposal no cooperation cooperation between nodes 5 / 13 Gwendal Simon Minimizing Server Throughput in CDN
14 Our proposal no cooperation cooperation between nodes Objectives : minimizing source throughput maintaining a low transmission delay 5 / 13 Gwendal Simon Minimizing Server Throughput in CDN
15 Rateless codes encoder decoder one chunk k symbols infinite nb. of encoded symbols k + ɛ symbols k decoded symbols 6 / 13 Gwendal Simon Minimizing Server Throughput in CDN
16 Rateless codes encoder decoder one chunk k symbols infinite nb. of encoded symbols k + ɛ symbols Main advantages : adaptive : no fixed code rate low complexity suitable for multi-source systems (Wu 2008) 6 / 13 Gwendal Simon Minimizing Server Throughput in CDN k decoded symbols
17 Multi-tree delivery (1/2) Main objective for the delivery of one video chunk : minimize the number of trees (packets) Main constraint in the trees : each node should be in K trees upload capacity constraint c on nodes 7 / 13 Gwendal Simon Minimizing Server Throughput in CDN
18 Multi-tree delivery (1/2) Main objective for the delivery of one video chunk : minimize the number of trees (packets) Main constraint in the trees : each node should be in K trees upload capacity constraint c on nodes s s s s s K = 3, c = {2, 2, 3, 1} 7 / 13 Gwendal Simon Minimizing Server Throughput in CDN
19 Multi-tree delivery (2/2) Additional constraints Do not introduce much delay sum of delays over all paths in any tree below D Do not introduce much packet loss overall probability of all paths in any tree below P 8 / 13 Gwendal Simon Minimizing Server Throughput in CDN
20 Our contributions Two algorithms : 1. without last constraints : an optimal O(Kn 2 ) algorithm 2. with limited tree height : an efficient O(Kn 3 ) heuristic 9 / 13 Gwendal Simon Minimizing Server Throughput in CDN
21 Our contributions Two algorithms : 1. without last constraints : an optimal O(Kn 2 ) algorithm 2. with limited tree height : an efficient O(Kn 3 ) heuristic Algorithm performances depend on the context : over-provisioned system source rate = video rate is achievable under-provisioned system source has to compensate missing resources 9 / 13 Gwendal Simon Minimizing Server Throughput in CDN
22 Simulations Video and rateless code settings : H.264 with bitrates from 320 kbps to 3.2 Mbps One chunk is one GOP : 0.5 seconds One UDP packet is 1,000 bytes Raptor code with redundancy 5% Network and node settings : from 5 to 25 nodes upload capacity follows log-normal distribution mean capacity is {512, 1,024, 2,048} kbps homogeneous packet loss probability and RTT 10 / 13 Gwendal Simon Minimizing Server Throughput in CDN
23 Scalability transmission rate (in kbps) 5,000 4,000 3,000 2,000 1, kbps number of nodes 11 / 13 Gwendal Simon Minimizing Server Throughput in CDN
24 Scalability transmission rate (in kbps) 5,000 4,000 3,000 2,000 1, kbps 1024 kbps number of nodes 11 / 13 Gwendal Simon Minimizing Server Throughput in CDN
25 Scalability transmission rate (in kbps) 5,000 4,000 3,000 2,000 1, kbps 1024 kbps 2048 kbps number of nodes 11 / 13 Gwendal Simon Minimizing Server Throughput in CDN
26 playback lag (in ms) Decoding lag 1, kbps 1024 kbps 2048 kbps number of nodes 12 / 13 Gwendal Simon Minimizing Server Throughput in CDN
27 Future works Real implementation. We currently have : a fully-developed program that just works some contacts with a small CDN company Academic work : resource management for multiple flows more dynamic algorithms 13 / 13 Gwendal Simon Minimizing Server Throughput in CDN
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