On Indexed Data Broadcast

We consider the problem of efficient information retrieval in asymmetric communication environments where multiple clients with limited resources retrieve information from a powerful server who periodically broadcasts its information repository over a communication medium. The cost of a retrieving client consists of two components: (a) access time, defined as the total amount of time spent by a client in retrieving the information of interest; and (b) tuning time, defined as the time spent by the client in actively listening to the communication medium, measuring a certain efficiency in resource usage. A probability distribution is associated with the data items in the broadcast representing the likelihood of a data item\u27s being requested at any point of time. The problem of indexed data broadcast is to schedule the data items interleaved with certain indexing information in the broadcast so as to minimize simultaneously the mean access time and the mean tuning time. Prior work on this problem thus far has focused only on some special cases. In this paper we study the indexed data broadcast problem in its full generality and design a broadcast scheme that achieves a mean access time oef at most (1.5 + ε) times the optimal and a mean tuning time bounded by O(log n)

On Indexed Data Broadcast

We consider the problem of efficient information retrieval in asymmetric communication environments where multiple clients with limited resources retrieve information from a powerful server who periodically broadcasts its information repository over a communication medium. The cost of a retrieving client consists of two components: (a) access time, defined as the total amount of time spent by a client in retrieving the information of interest; and (b) tuning time, defined as the time spent by the client in actively listening to the communication medium, measuring a certain efficiency in resource usage. A probability distribution is associated with the data items in the broadcast representing the likelihood of a data item\u27s being requested at any point of time. The problem of indexed data broadcast is to schedule the data items interleaved with certain indexing information in the broadcast so as to minimize simultaneously the mean access time and the mean tuning time. Prior work on this problem thus far has focused only on some special cases. In this paper we study the indexed data broadcast problem in its full generality and design a broadcast scheme that achieves a mean access time oef at most (1.5 + ε) times the optimal and a mean tuning time bounded by O(log n)

Achieving Marton's Region for Broadcast Channels Using Polar Codes

This paper presents polar coding schemes for the 2-user discrete memoryless broadcast channel (DM-BC) which achieve Marton's region with both common and private messages. This is the best achievable rate region known to date, and it is tight for all classes of 2-user DM-BCs whose capacity regions are known. To accomplish this task, we first construct polar codes for both the superposition as well as the binning strategy. By combining these two schemes, we obtain Marton's region with private messages only. Finally, we show how to handle the case of common information. The proposed coding schemes possess the usual advantages of polar codes, i.e., they have low encoding and decoding complexity and a super-polynomial decay rate of the error probability. We follow the lead of Goela, Abbe, and Gastpar, who recently introduced polar codes emulating the superposition and binning schemes. In order to align the polar indices, for both schemes, their solution involves some degradedness constraints that are assumed to hold between the auxiliary random variables and the channel outputs. To remove these constraints, we consider the transmission of $k$ blocks and employ a chaining construction that guarantees the proper alignment of the polarized indices. The techniques described in this work are quite general, and they can be adopted to many other multi-terminal scenarios whenever there polar indices need to be aligned.Comment: 26 pages, 11 figures, accepted to IEEE Trans. Inform. Theory and presented in part at ISIT'1

Interactive searching and browsing of video archives: using text and using image matching

Over the last number of decades much research work has been done in the general area of video and audio analysis. Initially the applications driving this included capturing video in digital form and then being able to store, transmit and render it, which involved a large effort to develop compression and encoding standards. The technology needed to do all this is now easily available and cheap, with applications of digital video processing now commonplace, ranging from CCTV (Closed Circuit TV) for security, to home capture of broadcast TV on home DVRs for personal viewing. One consequence of the development in technology for creating, storing and distributing digital video is that there has been a huge increase in the volume of digital video, and this in turn has created a need for techniques to allow effective management of this video, and by that we mean content management. In the BBC, for example, the archives department receives approximately 500,000 queries per year and has over 350,000 hours of content in its library. Having huge archives of video information is hardly any benefit if we have no effective means of being able to locate video clips which are of relevance to whatever our information needs may be. In this chapter we report our work on developing two specific retrieval and browsing tools for digital video information. Both of these are based on an analysis of the captured video for the purpose of automatically structuring into shots or higher level semantic units like TV news stories. Some also include analysis of the video for the automatic detection of features such as the presence or absence of faces. Both include some elements of searching, where a user specifies a query or information need, and browsing, where a user is allowed to browse through sets of retrieved video shots. We support the presentation of these tools with illustrations of actual video retrieval systems developed and working on hundreds of hours of video content