# Cooperative Buffering Schemes for Time-Shifted Live Streaming of Distributed Appliances
## 1 Introduction
Thus, as a PVR moves to an earlier position time-shifted from the live broadcast time, the number of PVRs playing back at the position reduces rapidly, making it difficult for the PVR to receive necessary data from neighbors. It is obvious that its playback quality worsens since it is harder to satisfy a minimum number of neighbor PVRs required for playback. When they are eventually unable to obtain necessary data due to lack of neighbor PVRs storing them, they have to receive them from servers. This situation keeps PVRs from using advantages of P2P technologies, including scalability and low cost. Figure 1: Typical popularity distribution of live broadcast TV programs. In this paper, we therefore propose efficient cooperative buffering schemes to provide streaming services without service disruption for time-shifted periods from the live broadcast time even when the number of PVRs playing back in these periods is not sufficient [15]. We have observed that, since PVRs playing TV programs back at the live broadcast time can receive broadcast signals directly through their tuners and decode them with hardware devices, they do not need to exchange data with other PVRs or buffer them. Thus, our proposed buffering schemes can utilize the idle resources of the PVRs playing back at the live broadcast time for buffering, cooperating with each other. If PVRs do not cooperate to buffer broadcast programs to support each other's time-shifting, they can time-shift only the parts of the programs that have been played back before. On the contrary, our buffering schemes enable people to watch any TV program from the beginning even if the broadcasting of the program has already started or even ended. That is, people can watch any broadcast program at any time, even on the channels they have not turned on before. To determine which chunks are to be buffered, our proposed _D_egree of _D_eficiency and _P_roximity (_D_DP_)-based scheme prioritizes all time ranges depending on two factors: how deficient the number of copies of chunks is at each time range and how close to the live broadcast time the time range is [16]. To further improve performance, the _R_atio of Playback _R_equests to Chunk Copies (_R_RC_)-based scheme considers the ratio of the number of actual requests to that of chunk copies already buffered. This scheme can evaluate the priority of each time range more accurately by evaluating the number of actual requests to be processed subsequently. By utilizing the existing resources efficiently without investing more in expanding service capacity of the system, our proposed schemes can further improve the performance of time-shifted live streaming system. They can also adaptively adjust their computation loads depending on request arrival rates and computation capacity of tracker servers. Furthermore, they can be leveraged to alleviate the resource consumption on CDNs when employing both P2P networks and CDNs. Through extensive simulations, we show that our proposed buffering schemes can significantly extend the time-shifting hours compared with when PVRs buffer the broadcast programs independently of each other. We also compare the performance of the two buffering schemes in terms of playback continuity and startup delay while varying the buffer size, playback request distribution, and the number of participating PVRs. This paper is organized as follows: Section 2 describes work related to this paper. Section 3 describes our two proposed buffering schemes in detail. Section 4 compares the experimental results of the two buffering schemes. Finally, Section 5 offers conclusions.