Network Coding-based Content Distribution in Cellular Access Networks

Transcription

1 IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks Claudio Fiandrino Dzmitry Kliazovich Pascal Bouvry Albert Y. Zomaya University of Luxembourg University of Sydney May 24, 2016

2 Motivation 4.4 billion people will use mobile cloud applications by 2017 $ billion market Mobile cloud applications: 90% of all mobile data traffic by 2019 % 19 % 17 % 15 % 14 % 12 % 10 % Non-Cloud Cloud 50% 81 % 83 % 85 % 86 % 88 % 90 % Figure: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 1 of 15

3 Mobile data traffic 30 EB 30.6 EB 1 EB Global Internet 2000 Mobile Networks 2014 Mobile Networks 2020 (per month) Figure: Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update, Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 2 of 15

4 The key idea Objective Optimizing information delivery of flows with overlapping or partially overlapping content Network Coding Geographically co-located users Mobile cloud applications content Location Based Services Maps Meteo Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 3 of 15

5 Scenario vnc-cell in Mobile Cloud Virtualization of network coding operations Buffer Network Coding S-GW P-GW Ue Mobile Cloud enodeb E-UTRAN MME Cloud Mobile Operator Network P-GW: Packet Data Network Gateway S-GW: Serving Gateway MME: Mobility Management Entity E-UTRAN: Evolved-Universal Terrestrial Radio Access Network Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 4 of 15

6 vnc-cell key aspects Monitor and cache in transit traffic Identify coding opportunities Coding Opportunities Information needed by two or more users delivered with a single coded transmission XOR to combine packets Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 5 of 15

7 Example UE-1 UE-2 MOBILE CLOUD APPLICATION Request content A Packet request Packet A UE-1 Send content A Packet A UE-1 Cache and forward A UE-1 Process and store A UE-1 Request content B Packet request Packet BUE-2 Send content B UE-2 Packet BUE-2 Cache and forward B UE-2 Request content B Process and store B UE-2 Packet request Packet BUE-1 Send content B UE-1 Check if B is in buffer Packet (A B) UE-1,UE-2 Coding (A B) UE-1,UE-2 Decode B using A UE-1 Decode A using B UE-2 Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 6 of 15

8 Example UE-1 UE-2 MOBILE CLOUD APPLICATION Request content A Packet request Packet A UE-1 Send content A Packet A UE-1 Cache and forward A UE-1 Process and store A UE-1 Request content B Packet request Packet BUE-2 Send content B UE-2 Packet BUE-2 Cache and forward B UE-2 Request content B Process and store B UE-2 Packet request Packet BUE-1 Send content B UE-1 Check if B is in buffer Packet (A B) UE-1,UE-2 Coding (A B) UE-1,UE-2 Decode B using A UE-1 Decode A using B UE-2 Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 6 of 15

9 Example UE-1 UE-2 MOBILE CLOUD APPLICATION Request content A Packet request Packet A UE-1 Send content A Packet A UE-1 Cache and forward A UE-1 Process and store A UE-1 Request content B Packet request Packet BUE-2 Send content B UE-2 Packet BUE-2 Cache and forward B UE-2 Request content B Process and store B UE-2 Packet request Packet BUE-1 Send content B UE-1 Check if B is in buffer Packet (A B) UE-1,UE-2 Coding (A B) UE-1,UE-2 Decode B using A UE-1 Decode A using B UE-2 Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 6 of 15

10 Content distribution Optimal allocation for content distribution u k ck,k c2k,k Users u 2 c2,2 ck+2,2 cn,k c1,1 c2,2 cn k+1,2 ck 1,k 1 ck,k ck+1,1 ck+2,2 c2k 1,k 1 c2k,k cn k,1 cn k+1,2 cn 1,k 1 cn,k u 1 c1,1 ck+1,1 cn k,1 Individual Transmission - Encoded Transmission t Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 7 of 15

11 Setting NS-3 Simulations Num. users: 2-10 Chunk request rate: uniformly distributed between and 200ms Chunk size: 50 Bytes UDP transmissions IP Header UDP Header Chunk Header Chunk Payload ChunkId EncIdA EncIdB Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 8 of 15

12 Evaluation Metrics Number of transmissions performed by enodeb Individual and encoded transmissions Number of transmissions received by mobile users Download time comparison Distribution of transmissions in presence of channel errors Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 9 of 15

13 Number of transmissions performed by enodeb Num. transmissions vnc-cell Individual vnc-cell Encoded No vnc-cell Num. users Individual transmissions remains almost constant Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 10 of 15

14 Individual and encoded transmissions Num. transmissions Num. users Simulation time (s) Num. transmissions Num. users Simulation time (s) Encoded transmission higher when buffer in mobile cloud fills up Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 11 of 15

15 Number of transmissions received by mobile users Num. transmissions Content packets vnc-cell Individual vnc-cell Encoded Num. users Users receive more encoded packets than needed for the content Increase in reliability Increase in cost for decoding Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 12 of 15

16 Download time comparison 80 vnc-cell NO vnc-cell Download time (s) Num. chunks 4 users download 500 chunks randomly from a chunk file vnc-cell still achieves approximately 10% shorter download times Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 13 of 15

17 Distribution of transmissions with channel errors Num. transmissions Distance from enodeb (m) Num. users Num. transmissions Distance from enodeb (m) Num. users Distance from enodeb (m) Content Individual Encoded Num. transmissions Num. users COST-Hata model vnc-cell is scalable and resilient to errors Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 14 of 15

18 Conclusion Summary Efficient content distribution for cloud applications Network coding and caching performed at mobile cloud Take home message Download time gain Scalable and resilient to errors Claudio Fiandrino IEEE ICC 2016 Network Coding-based Content Distribution in Cellular Access Networks 15 of 15

19 Thank Thank You! You! Claudio Fiandrino