End-to-End Analysis of Distributed Video-on-Demand Systems P. Mundur, R. Simon, and A. K. Sood IEEE Transactions on Multimedia, Vol. 6, No. 1, Feb 2004.

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End-to-End Analysis of Distributed Video-on-Demand Systems P. Mundur, R. Simon, and A. K. Sood IEEE Transactions on Multimedia, Vol. 6, No. 1, Feb 2004 Presented by Ho Tsz Kin 10/03/2004

Agenda Introduction System Model Admission Control Request Handling Performance Evaluation Conclusion

Introduction Distributed VoD architecture with replication Model and analyze subsystems – server, network, client Design End-to-end admission control techniques Request handling Strategies Objective Minimize the number of blocked requests

Hierarchical VoD Architecture Mirrored sites Provide video delivery to many user population Cluster of video servers Limited bandwidth Replicated video No contention Decoding, buffering and display Contention exists

Streaming Model Primary service provider Delivery over local network only Secondary service provider Delivery over high speed network Redirecting to other remote sites Admission control test

Server and Network Model High capacity and bandwidth disk array Double buffer scheme Order serving by the disk is not important (b, r, p, M) Traffic regulator b: token bucket size r: token accumulation rate p: peak rate of NIC M: max. packet size for the flow

Server and Network Model (b, r, p, M) Traffic regulator In any interval x 0, bytes at its output is min(M+px, b+rx) Control the burstiness of the flow into the network WFQ scheduling Implemented in the network Provide a firm per-packet end-to-end delay bound on a per-link and per-routing path RSVP Reserve resources along the path of the requests

Admission Control Derive admission control conditions at the server and network Using (b, r, p, M) traffic regulator, and WFQ b = B r, r = R r, p defaults infinity Max. bounded end-to-end delay Retrieval block size Network reserved rate Routing path with J links Max packet size Overall bandwidth on j th link Max packet size permitted in network (MTU)

Admission Control New request will be admitted only if Reserved rate for new request Admission control tests run on link by link basis over the routing path

Request Handling redirect blocked request at one resource is simply redirected to other resources higher implementation overhead additional setup time split-based fixed load-sharing among resources simpler implementation difficult to determine efficient splits

Performance Evaluation Simulation Data and Model Metrics: Blocking rate, Blocking probability

Performance Evaluation Admission control test Request handling policies Redirect LocalRemote1Remote2 Request Blocked

Performance Evaluation Split-x-y First split between local and remote clusters in ratio of x and (100 - x) Further split between remote cluster1 and cluster2 in ratio of y and (100 - y) Split-redirect -x-y Blocked requests in local are redirected to remote cluster1 Blocked requests in remote cluster1 are NOT redirected to remote cluster2

Performance Evaluation Single rate playback service (8Mbps) 750 streams by local server, 311 streams per remote cluster Replicated locally (2.5TB storing 800GB)

Performance Evaluation Crossover By proportion of traffic directed toward the local cluster Divergence By proportion of traffic directed toward the remote traffic

Performance Evaluation Blocking performance at individual resources

Performance Evaluation Efficient split Choosing split value that are close to the proportion of resource capacities Possible only if the portion of remote cluster capacity is known In general, difficult to determine One-level redirection already achieves better

Performance Evaluation Scalability issue Overall blocking stabilizes gradually remain constant

Performance Evaluation Replication issue 1 st scenario: single server in the local cluster, top 30 videos stored locally 2 nd scenario: five servers in the local cluster, top 30 videos stored locally, 5 times replication allowed 3 rd scenario: five servers in the local cluster, complete video collection stored locally

Performance Evaluation Fairness Only partial list of top videos are stored on the local cluster with five video server Class1: top 20% videos Class2 & 3: other 80% Redirect at 1000 requests per hour

Conclusion & Discussion Analyzed VoD system with a hierarchy of servers and network elements Derived the admission control condition Using extensive simulation, designed and evaluated several request handling policies Redirect will be more suitable Discussion QoS guaranteed networks Other network traffic exists, and more remote sites Difficult to determine the split percentage Reliability issue