Transport capacity for a catch-up television service

One of the biggest advantages of interactive television (TV) is that it allows the viewer to watch the content at his or her most convenient time, either by pausing an ongoing broadcast or by selecting to view the content at a time later than the original airing time. The former service, often referred to as Pause Life TV (PLTV), and the latter, often referred to as Catch-Up TV (CUTV), require that an individual unicast flow is set up per user, whereas for the traditional Linear Programming TV (LPTV) the user just tunes in to a multicast flow that can serve many viewers. We first show that when services like PLTV and CUTV gain in popularity, the transport capacity required in certain parts of the network risks to grow unwieldy, unless the content is replicated (i.e., cached) in the appropriate places in the network. Subsequently, we show that a good caching algorithm that tracks the evolving popularity of the content and takes into account the initial popularity, allows keeping the required capacity under control. Finally, we discuss the trade-offs involved in determining the optimal cache location.One of the biggest advantages of interactive television (TV) is that it allows the viewer to watch the content at his or her most convenient time, either by pausing an ongoing broadcast or by selecting to view the content at a time later than the original airing time. The former service, often referred to as Pause Life TV (PLTV), and the latter, often referred to as Catch-Up TV (CUTV), require that an individual unicast flow is set up per user, whereas for the traditional Linear Programming TV (LPTV) the user just tunes in to a multicast flow that can serve many viewers. We first show that when services like PLTV and CUTV gain in popularity, the transport capacity required in certain parts of the network risks to grow unwieldy, unless the content is replicated (i.e., cached) in the appropriate places in the network. Subsequently, we show that a good caching algorithm that tracks the evolving popularity of the content and takes into account the initial popularity, allows keeping the required capacity under control. Finally, we discuss the trade-offs involved in determining the optimal cache location.P