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On Zap Time Minimization in IPTV Networks International Conference on Computing, Networking and Communications, Internet Services and Applications Symposium On Zap Time Minimization in IPTV Networks Matthew Long, Sridhar Radhakrishnan, Suleyman Karabuk, John Antonio School of Computer Science School of Industrial Engineering School of Computer Science University of Oklahoma University of Oklahoma University of Oklahoma Norman, Oklahoma 73019 Norman, Oklahoma 73019 Norman, Oklahoma 73019 E-mail: {mglong, sridhar}@ou.edu E-mail: [email protected] E-mail: [email protected] Abstract—Digital television systems have a clear disadvantage state-of-the-art. These advantages include a) wherever Internet relative to analog systems in users’ quality of experience, most access is available, broadcast channels can be delivered and notably in the time required to change channels, or zap time. this eliminates the need for additional infrastructure (such as The goal of this research is to improve the performance of a multicasting IPTV network, both in user experience and in cable or satellite), b) the broadcast content can be viewed on resource consumption. We formulate the problem of assigning any device that has an Internet connection and appropriate IPTV clients to servers as an integer programming model, in video display without the need for specialized STB hardware, variants which minimize channel-change times, overall network and c) bandwidth can be conserved as only the users watching capacity consumption, or both. This problem is shown to be a particular channel need to receive it. Several organizations computationally hard, and the performance of the models is tested on problems of different sizes. Polynomial-time heuristics have set standards for implementing IPTV networks, including are presented which address a relaxed version of the problem, ETSI TISPAN, the DVB Project, and the Open IPTV Forum and the performance of these heuristics is measured. [2], [13], [1]. These standards define functionality, protocols, Index Terms—IPTV Networks, Multicast, Integer Program- and architectures for IPTV systems. IPTV standards typically ming, NP-Hardness include Video on Demand (VoD) functionality in addition to “broadcast” channels, but VoD is outside the scope of this I. INTRODUCTION paper. There has been explosive growth in video traffic on the While there are significant advantages to IPTV, it suffers Internet due to a combination of an increase in the number from long zap times. Imagine a user on a laptop computer of video content providers, ubiquity of devices capable of switching between broadcast channels. Each time the user viewing video content, and keen interest among the viewing switches to a different channel, a program on the laptop will public. Video on the Internet is either broadcast (e.g., NBC’s establish a connection to a server in the IPTV network and wait streaming of the Olympic Games) or provided on demand for the new channel to begin streaming from it. This delay is (e.g., Netflix and Hulu’s services). proportional to the network latency between the laptop and Cable companies deliver all broadcast channels to the end the contact server. Depending on the location of the server, system (e.g., a set-top box, or STB) at home and, depending this delay will vary, and the greater this delay, the lesser the upon the subscription criteria, a subset of these channels are Quality of Experience (QoE) for the end user. viewable by the end user. In this scheme the cable company The goal of this research is to improve QoE in an IPTV streams as many channels as can be accommodated on the network by minimizing zap time and bandwidth consumption. cable. This is true of satellite television, which also requires a Towards this goal, we consider a network of servers connected specialized STB to deliver content and delivers all broadcast to form a rooted tree (a multicasting tree) with network delay channels to the end system. The significant advantage of and bandwidth specified on each link, and a set of clients, systems that broadcast all channels is that the user experiences each of which requires a subset of the channels carried by the almost no delay when changing channels, as the content is tree. (Each client has a network delay defined between it and already being delivered to the user’s STB. The time interval each server.) One can imagine these intermediate servers to between the user keying in the change channel request and the be connected to end offices of Internet Service Providers and display of the contents of the new channel on the user’s screen hence be well-provisioned, with minimal server-to-server link is termed as the zap time. For analog cable and satellite tele- delays. The root of the tree is the server, r, that is the source of vision viewers, the zap time is insignificant. Digital broadcast all channels. Each intermediate node may duplicate the content systems require additional time to buffer and begin decoding it receives from its parent and send it to a subset of its children the compressed channel, and therefore have somewhat longer in the tree. To conserve bandwidth, a node only redistributes zap times. channels to those of its children who request them. If a server There has been a growing interest in delivering broadcast k is receiving a particular channel c, then all servers in the video channels through the Internet (or other IP networks). path from k to r have channel c, and can immediately satisfy Broadcast channels delivered via an IP network is termed any request for it. as IPTV. IPTV offers significant advantages over the current A client is an end system that has requests for a set of 978-1-4673-0009-4/12/$26.00 ©2012 IEEE 713 channels. (For example, each client may have a set of favorite Cha et al. [7] and Qiu et al. [14] have investigated channel channels collected over time or a set of channels to which popularity dynamics in IPTV systems. Both papers used large it subscribes.) Each client has to connect to the appropriate channel-change datasets from actual IPTV networks. Cha server (introducing network delay) for each of its channel found that more than 60% of channel changes are linear; i.e., to requests. Now, given a multicasting tree as above and a set of the next- or previous-numbered channel. Both concluded that clients with channel requests, our goal is to find the appropriate channel popularity distributions resemble a Zipf distribution, server for each client to connect to for each of its channel with the few most popular channels accounting for most of requests. (Because bandwidth is a limited, potentially shared the viewing. Qiu’s main contributions were improved mathe- resource, specifying that every server carries every channel is matical models of user behavior, which have the potential to not an option.) improve simulations of IPTV systems in further research. We first develop a series of mixed integer programming (MIP) models of our problem. We then show that the problem II. PRELIMINARIES is NP-hard. We show the results of solving many problem The Client Assignment Problem (CAP) is defined as the instances. Toward a scalable solution to these problems, we satisfaction of a set of demands for channels (or, equivalently, provide polynomial-time heuristic algorithms for a relaxed channel requests) by assigning each demand to be fulfilled version of the problem, which take into consideration various by a node of a multicasting tree (i.e., an IPTV network). A tradeoffs between link capacity and zap time. These heuris- client’s channel requests need not be satisfied by the same tics have been evaluated empirically using many problem server; fulfilling requests from a client with different servers instances. can use fewer network resources or provide better zap time than fulfilling them with a single server. (A client could request A. Related Work multiple channels for a variety of reasons; e.g., picture-in- Zap time is the channel change time as perceived by picture or multi-channel recording.) Channels are assumed the viewer. Its primary components are multicast join time, to require equal bandwidth, so server-server link capacities network latency, buffering and decoding, error correction, and (bandwidths) are given in units of channels. Additionally, all access control [10], [17]. Zap time is a major factor in the components of zap time other than round-trip time are ignored viewer’s Quality of Experience (QoE): both shorter zap times (e.g., buffering and decoding delays). The CAP is an offline and consistency in zapping are preferred. problem; demands are unordered and are known in advance. A client needs to buffer a certain amount of data to decode CAP shares some characteristics with facility location and the channel stream; this buffer must begin with a random network flow problems, but differs from them in several ways. access point (RAP). A RAP is a block of the stream that is Facility location (FL) problems involve placing facilities to independent of the rest of the stream; e.g., an I-frame. (Most serve clients. The location of facilities (once placed) and video frames are not transmitted in full; displaying such frames clients are fixed. The cost of serving a client is a function requires reference to previous or subsequent frames.) There of the distance between the facility and the client. There are are two ways to reduce the time to fill the decoder’s buffer: multicommodity variants of FL, in which clients may demand the encoding of the stream could be changed such that less different kinds of goods or services, and capacitated variants, buffering is required, or the buffer could be filled faster. Video in which a facility’s ability to produce is limited. The critical encodings can be adjusted to balance bandwidth consumption difference between (multicommodity, capacitated) FL and a and buffering requirements by varying the frequency of RAPs multicasting IPTV network is that FL features no relation- within the stream.
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