IPTV services deployed nowadays often consist of both live TV and Video-on-Demand (VoD), offered by the same service provider to the same pool of users over the same managed network. Understanding user behaviors in such a setting is hence an important step for system modelling and optimization. Previous studies on user behavior on video services were on either live TV or VoD.For the first time, we conduct an in-depth large-scale behavior study for IPTV users offering simultaneously live TV and VoD choices at the same time. Our data is from the largest IPTV service provider in China, offering hundreds of live channels and hundreds of thousands of VoD files, with traces covering more than 1.9 million users over a period of 5 months. This large dataset provides us a unique opportunity to cross-compare user viewing behaviors for these services on the same platform, and sheds valuable insights on how users interact with such a simultaneous system.Our results lead to new understanding on IPTV user behaviors which have strong implications on system design. For example, we find that the average holding time for VoD is significantly longer than live TV. live TV users tend to surf more. However, if such channel surfing is discounted, the holding times of both services are not much different. While users in VoD tend to view HD longer, channel popularity for live TV is much less dependent on its video quality. In contrast to some popular assumptions on user interactivity, the transitions among live TV, VoD, and offline modes are far from a Markov model.

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Among video application use cases and scenarios, 360-degree video applications gradually become significant. The state-of-the-art solution for 360-degree video streaming is field of view (FOV) transmission, whose quality of experience highly depends on system processing speed and network latency. The extant 360-degree video FOV transmission profiles transmit multiple video tile streams to the client over either Hypertext Transfer Protocol (HTTP) or Real Time Streaming Protocol (RTSP). The client needs to merge all different tile streams after receiving them, which may cause a data synchronization problem of waiting for each tile to sync in the presents of packet losses. Therefore, we propose a system to select and merge tile streams on the Content Delivery Network (CDN) server and transmit the merged stream to the client. During the streaming service, the client can send a viewport switch request through RTSP signaling, and the server will subsequently deliver the merged video stream of the new viewport to the client after receiving the request. Also, to reduce disk overhead from parallel reads, we optimize the system with a file prefetch strategy to reduce unorganized, random, and parallel reads into serialized reads of large data trunks. We evaluate its performance through user request simulation experiments. Compared with the extant transmission solution, our system provides slightly lower video transmission latency, lower central processing unit (CPU) usage, and better disk performance under heavy service load.

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