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SS-VoD over TVoD UVoD over TVoD
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Figure 19.14 Channel reduction over TVoD at very low arrival rates
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60 50 40 30 20 10 0 Resource Increases (%)
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Number of Channels Required
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Variable Service Time Worst-case Service Time Resource Increases
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1 1.5 2 Arrival Rate (requests/second)
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Figure 19.15 Performance trade-off for using worst-case service time for dynamic channels
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SS-VoD require only six channels. This suggests that SS-VoD will likely outperform TVoD in practice.
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19.4.6 Simplicity versus Performance Trade-off
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The admission controller is among the more complex components in the SS-VoD architecture. One way to simplify the admission controller is to use a constant service time of TR 2 seconds for the dynamic channels. As this is the worst-case service time, the admission controller no longer needs to maintain the counter-length tuple {AC , A L } and also does not need to send an EXTEND update request to the service node. The trade-off for this simpli cation is increased channel requirement as the dynamic channel will be occupied for a time longer than necessary. Figure 19.15 compares the two cases, showing that using the worst-case service time of TR 2 seconds results in resource increases of over 30%. This shows that the more complex admission procedure is still desirable unless system complexity must be minimized.
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19.5 Implementation and Benchmarking
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We implemented a SS-VoD prototype using off-the-shelf software and hardware. There are three components in the prototype: service node, admission controller, and video clients. Both the service node and the admission controller are implemented using the C++ programming language running on Red Hat Linux 6.2. Two client applications have been developed, one is implemented using the Java programming language and the Java Media Framework (JMF) 2.1, while the other is implemented using C++ on the Microsoft Windows platform. Both the service node and the admission controller are video format independent. The Java-version client supports MPEG1 streams, while the Windows-version client supports MPEG1, MPEG2, as well as basic MPEG4 streams. We also implemented the interactive playback controls presented in Section 19.2, namely pause resume, slow motion, and seeking.
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A Hybrid Architecture
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Analytical Results Simulation Results Experimental Results
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Figure 19.16 Comparison of latencies obtained from analysis, simulation and benchmarking
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With the SS-VoD prototype, we conducted extensive experiments to obtain measured benchmark results to verify against the analytical and simulation results. We developed a traf c generator in order to simulate a large number of client requests. The service node runs on a Compaq Proliant DL360 serving one movie of length 120 minutes with 30 channels, each at 1.5Mbps. The clients are ordinary PCs and all machines are connected using a layer-3 IP switch with hardware IP multicast support. We measured the start-up latency for arrival rates ranging from 1 to 5 requests per second. Each benchmark test runs for a total of six hours. Benchmark data collected during the rst hour is discarded to reduce initial condition effect. Figure 19.16 compares the start-up latencies obtained from analysis, simulation, and benchmarking respectively. We observe that the benchmarking results agree very well with the analytical results and simulation results. Note that the latencies obtained from benchmarking are consistently larger than those obtained from simulation. We believe that this is due to the non-zero processing delay and network delay in the system, both of which have been ignored in the simulation model.
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19.6 Summary
In this chapter, we investigated a Super-Scalar Video-on-Demand (SS-VoD) architecture that can achieve super-linear scalability by integrating techniques of batching, patching, and periodic broadcasting. In designing the SS-VoD architecture the focus is on its practicality and the implementation and deployment complexities. For example, instead of adopting more sophisticated open-loop algorithms to schedule the static multicast channels, we employed the simple staggered periodic multicast schedule that enables us to implement interactive playback control such as pause resume, slow motion, and seeking in a simple yet ef cient way. Moreover, the staggered schedule also requires signi cantly lower client buffer requirement and more importantly, eliminates the need to switch multicast channels during a video session.