Consider a source broadcasting Ml pack-other hand, use of coding nmay allow to achieve higher inets to N receivers over independent erasure channels, fornmation rates, thus reducing the delay. Thus rate and where perfect feedback is available from the receivers delay are clearly intertwined quantities. to the source, and the source is allowed to use coding.We define a schenme to be rate-optimal if every suc-We investigate offline and online algorithms that op-cessfully received packet brings new infornmation to its timize delay, both through theoretical analysis as well receiver. We say that a scheme has zero delay, if it is as simulation results. rate optimal, and additionally, each receiver can instantaneously decode an inforination packet froin each received I. INTRODUCTION 978-1-4244-1689-9/08/$25.00 ©2008 IEEE

We consider the problem of minimizing delay when broadcasting over erasure channels with feedback. A sender wishes to communicate the same set of µ messages to several receivers over separate erasure channels. The sender can broadcast a single message or a combination (encoding) of messages at each timestep. Receivers provide feedback as to whether the transmission was received. If at some time step a receiver cannot identify a new message, delay is incurred. Our notion of delay is motivated by real-time applications that request progressively refined input, such as the successive refinement of an image encoded using multiple description coding. Our setup is novel because it combines coding techniques with feedback information to the end of minimizing delay. It allows Θ(µ) benefits as compared to previous approaches for offline algorithms, while feedback allows online algorithms to achieve smaller delay than online algorithms without feedback. Our main complexity results are that the offline minimization problem is N P-hard when the sender only schedules single messages and that the general problem remains N P-hard even when coding is allowed. However we show that coding does offer delay and complexity gains over scheduling. We also discuss online heuristics and evaluate their performance through simulations.

Abstract-In networks that employ network coding, two main approaches have been proposed in the literature to allow the receivers to recover the source information: (i) use of coding vectors, that keep track of the linear combinations the received packets contain, and (ii) subspace coding, that dispenses of the need to know the linear combinations, since information is conveyed from the choice of subspaces alone. Both these approaches impose the strong requirement that all source packets get potentially combined. We here present a third approach that relaxes this assumption, and is thus not a special case from either of the previous two. This relaxation allows to employ compressed coding vectors to efficiently convey the coding coefficients, without altering the operation of intermediate network nodes. We develop optimal designs for such vectors.

Abstract-Video applications are increasingly popular over smartphones. However, in current cellular systems, the downlink data rate fluctuates and the loss rate can be quite high. We are interested in the scenario where a group of smartphone users, within proximity of each other, are interested in viewing the same video at the same time and are also willing to cooperate with each other. We propose a system that maximizes the video quality by appropriately using all available resources, namely the cellular connections to the phones as well as the device-todevice links that can be established via Bluetooth or WiFi. Key ingredients of our design are: (i) the cooperation among users, (ii) network coding, and (iii) exploiting broadcast in the mobileto-mobile links. Our approach is grounded on a network utility maximization formulation of the problem. We present numerical results that demonstrate the benefit of our approach, and we implement a prototype on android phones.

We consider a group of mobile users, within proximity of each other, who are interested in watching the same online video at roughly the same time. The common practice today is that each user downloads the video independently on her mobile device using her own cellular connection, which wastes access bandwidth and may also lead to poor video quality. We propose a novel cooperative system where each mobile device uses simultaneously two network interfaces: (i) the cellular to connect to the video server and download parts of the video and (ii) WiFi to connect locally to all other devices in the group and exchange those parts. Devices cooperate to efficiently utilize all network resources and are able to adapt to varying wireless network conditions. In the local WiFi network, we exploit overhearing, and we further combine it with network coding. The end result is savings in cellular bandwidth and improved user experience (faster download) by a factor on the order up to the group size.We follow a complete approach, from theory to practice. First, we formulate the problem using a network utility maximization (NUM) framework, decompose the problem, and provide a distributed solution.Then, based on the structure of the NUM solution, we design a modular system called MicroCast and we implement it as an Android application. We provide both simulation results of the NUM solution and experimental evaluation of MicroCast on a testbed consisting of Android phones. We demonstrate that the proposed approach brings significant performance benefits without battery penalty.