Performance Evaluation of Peer-to-Peer Video Streaming Systems Wilson, W.F. Poon The Chinese University of Hong Kong

Content Introduction Related Works System Model Experimental Results Conclusion

Introduction (1) Providing video streaming services have long been a research topic – parallel server designs such as RAID – multicast/broadcast transmission schemes – distributed VoD systems Tremendous growth in computer power of personal computers – peer-to-peer (p2p) systems – Peers contribute storage, content and bandwidth

Introduction (2) Most of these p2p systems have been developed for file sharing/web caching services – Search mechanism – Storage management Maximize file availability or system reliability The work on p2p video streaming has not been thoroughly studied Investigate whether such a p2p system is applicable to supporting video streaming applications – Distributed data storage and its impact on streaming performance – Analytical framework incorporated the effect of data replication and placement policies

P2P Streaming Systems (1) One of major challenges of a p2p system – Peer machines may be turned on and off in an unpredictable manner – The system experiences very worse availability video replica replica Full Replication serving peer free rider Replication

P2P Streaming Systems (2) A network has G peers in which I peers (serving peers) stores a set of J different videos The other peers (free riders) just make requests but not contribute their resources Assume –  is the “up” probability of the peers – T up is the mean up time duration – T down is the mean down time duration Assume – N i is the amount of shared storage in peer i – b j is the size of video j – q j is the request probability for video j – C j is the bit rate for video j

P2P Streaming Systems (3) n j is the number of replicas for video j, v j Requests to a serving peer for v j is given by System storage constraints

System Availability With full replication scheme – The video j is not available when all the peers storing v j are off-line simultaneously System Availability

System Arrival (1) peer peer i requested video available Playback is unsuccessful if the request is blocked rejected Availability

System Arrival (2) New requests to peer i Requests partially served by peer i Probability of requests redirected Probability of requests blocked V i : Set of videos stored in peer i

System Arrival (3) Assume – Service time (video length) follows an exponential distribution – “up” duration is exponentially distributed Probability of requests redirected by the “up” peer L: mean video length T up : mean “up” time duration

System Arrival (4) Total partially served traffic Redirect requests to peer k

System Arrival (5) where

System Arrival (6) The equations can be represented Redirect arrivals can be solved

System Blocking (1) Unsuccessful playback – Proportion of requests that cannot completely playback the whole video Assume – Poisson Arrival Process – Video length, “up” and “down” durations follow exponential distribution States of peer i can be represented by a Markov Model

System Blocking (2) OFF ON/0 ON/1ON/2 ON/K Peer’s state diagram

System Blocking (3) Since a peer will not receive any requests (new/redirect) in “off” state, the probability of requests blocked by a peer is equal to

System Blocking (4) A new video request may be redirected by peers several times to finish the video playback If either the new request or the redirected request is blocked, the playback is considered to be unsuccessful

Experimental Results Simulation is built to verify the model – Randomly determine the number of replicas for each video (random replication) – Randomly store the replicas among peer (random placement) – Video popularity follows a Zipf distribution with parameters – Mean video length is 2 hours – T up + T down = 10 hours Measure the unsuccessful playback rate – Peers cannot complete the video playback

Results – Arrival Rate  Number of peers=1200  Number of videos=200  Video length=7200s

Results – Serving Peers  Arrival rate=0.04/s  Number of videos=200  Video length=7200s

Results – Peer Availability  Arrival rate=0.02/s  Number of peers=1200  Number of videos=200  Video length=7200s

Replication Strategy - MinReq For video streaming, a request that can be served requires: – The requested video is available in the system – The serving peers have the available bandwidth Determine the number of video replicas by minimizing the load of the serving peers Subject to Minimize: Optimal replication profile:

Results – Serving Peers (MinReq)  Arrival rate=0.04/s  Number of videos=200  Video length=7200s  Peer Storage=10

Error on Video Popularity Considering an estimation error Estimated popularity is used to generate the replication profile

Results – Estimation Error  Arrival rate=0.04/s  Number of videos=200  Video length=7200s

Conclusion Consider the performance of a p2p system for video streaming services Evaluate data storage and its impact on video streaming Develop analytical framework to capture the properties of the system – Data replication – placement policy Optimal replication scheme may not significantly improve the successful playback rate