Enhancing Software-Defined RAN with Collaborative Caching and Scalable Video Coding

Transcription

1 Enhancing Software-Defined RAN with Collaborative Caching and Scalable Video Coding Ruozhou Yu, Shuang Qin, Mehdi Bennis, Xianfu Chen, Gang Feng, Zhu Han, Guoliang Xue

2 Agenda Introduction Problem Formulation Solution Design Performance Evaluation Conclusions 2

3 Software-Defined RAN Decoupled control & data planes. Control Plane Data Plane Centrally managed resources and info. Opportunity for inter-bs collaboration. Global optimization for content delivery 3 Radio Resource Storage Resource Backhaul Bandwidth Channel Info Traffic Requests User Preferences

4 Video Caching in RAN Video 1 request Video 2 request Video 3 request 4

5 Video Caching in RAN Video 1 request Video 2 request Video 3 request 5

6 Collaborative Caching Video 1 request Video 2 request Video 3 request 6

7 Scalable Video Coding (SVC) Videos have different bitrate versions: 360p, 720p, 1080p, etc. SVC slices video into different layers: Base layer guarantees the minimum bitrate playback Each enhancement layer increases bitrate by one level Enh. BR 4 Enh. BR 2 Base BR Layering Constraint: to get enhanced BR l, both the base layer and all enhancement layers below l are needed. Base Layer Enh. Layer 1 Enh. Layer 2 Enh. Layer 3 Enh. Layer 4 Enh. Layer 5 7 Enh. BR 1 Enh. BR 3 Enh. BR 5

8 Agenda Introduction Problem Formulation Solution Design Performance Evaluation Conclusions 8

9 Problem Overview Generally, given the network status and some prediction on user s video requests, we want to decide two things: 1) which base station s cachestores which layersof which video, and 2) how to schedule (route) the video streams of eachrequest, such that we maximize the number and qualityofvideos served, meanwhile minimizing the delayreceived by users. 9

10 Network Model Base stations B={B 0,, B M } Cache size c i Upstream/downstream backhaul bandwidth b i u /b i d B 0 denotes the Internet with unlimited cache and bandwidth Distance between two BSs d i,ɩ Videos V ={V 1,..., V N } Layers L j = {1,..., L j } for each video V j Layer size s j l Layer bandwidth requirement β j l ψ ɩ j,l : number of users at BS B ɩ, requesting the first l layers of video V j 10

11 Variables x i j,l : indicator ofcaching video V j s layer l at BS B i z i,ɩ j,l : number of video V j s layer l requested byusers from BS B ɩ and served by the cache of BS B i 11

12 Objectives r j,lb : unit reward for serving video V j s layer l to user; c jd : unit cost for incurring delayfor video V j Objective: d ɩ j : aggregated delay received by video V j s user(s) at BS B ɩ 12

13 Constraints 13

14 Constraints cont. 14

15 Agenda Introduction Problem Formulation Solution Design Performance Evaluation Conclusions 15

16 Algorithm Overview Two stages: Stage 1: decide the caching of videos (layers) at each base station; Stage 2: decide which base station serves each layer of each user s request, based on the Stage 1 results. Rounding-based algorithm: Relax the ILP formulation to LP; Solve for a (fractional) solution; Use deterministic rounding technique to obtain anintegral solution. 16

17 Stage 1: Video Caching Form ILP formulation and get LP relaxation Solve LPand obtain fractional solution Compute each variablex s contribution towards objective Greedily round the caching variable x in sorted order Output caching decisions 17

18 Stage 2: Video Scheduling Form LP with fixed caching variables x Solve LPand obtain fractional solution Round down each scheduling variable z to obtain a basic solution More can be scheduled? NO YES Output scheduling decisions Schedule more requests via backhaul 18

19 Agenda Introduction Problem Formulation Solution Design Performance Evaluation Conclusions 19

20 Setup Randomlygenerated RANenvironment: 15 BSs users uniformly distributed 5000 videos with Zipf popularity distribution: ɣ= layers per video: 10% coding overhead introduced Randomly generatedcache, video size and bandwidth capacity/demands Five schemes for comparison: SC: SVC + Collaborative caching SS: SVC + Single BS caching NC: Non-SVC + Collaborative caching NS: Non-SVC + Single BS caching NN: Non-SVC + No caching 20

21 Exp. With Default Parameters 21

22 Active Users 22

23 Average Layers (Bitrates) 23

24 Average Delay 24

25 Agenda Introduction Problem Formulation Solution Design Performance Evaluation Conclusions 25

26 Conclusions Enhancingvideo deliveryin software-defined RANwith collaborative caching andsvc. Collaborative caching to reduce user delay; SVC to increasecachereuseand serve moreusers. Maximizing rewards and minimizing delay:a joint problem. NP-hard 2-stage rounding-based algorithm. Decide caching first. Schedule videos based on caching. Outperforms using either collaborative caching or SVC alone. 26

27 Thank You Q&A 27