MicroCast: Cooperative Video Streaming Using Cellular and Local Connections

We consider a group of mobile users, within proximity of each other, who are interested in watching the same online video. 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) 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 to exchange those parts. Devices cooperate to efficiently utilize all network resources and to adapt to varying wireless network conditions. In the local WiFi network, we exploit overhearing, which we further combine with network coding. The end result is savings in cellular bandwidth and improved user experience. 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 system called MicroCast, and we implement a prototype as an Android application. We provide both simulation results of the NUM solution and experimental evaluation. We demonstrate that the proposed approach brings significant performance benefits (namely, faster download on the order of the group size) without battery penalty.

MicroCast: Cooperative Video Streaming on Smartphones

Christina Fragouli, Lorenzo Keller

Video streaming is one of the increasingly popular, as well as de- manding, applications on smartphones today. In this paper, we con- sider a group of smartphone users, within proximity of each other, who are interested in watching the same video from the Internet at the same time. The common practice today is that each user down- loads the video independently using her own cellular connection, which often leads to poor quality. We design, implement, and evaluate a novel system, MicroCast, that uses the resources on all smartphones of the group in a co- operative way so as to improve the streaming experience. Each phone uses simultaneously two network interfaces: the cellular to connect to the video server and the WiFi to connect to the rest of the group. Key ingredients of our design include the follow- ing. First, we propose a scheduling algorithm, MicroDownload, that decides which parts of the video each phone should download from the server, based on the phones’ download rate. Second, we propose a novel all-to-all local dissemination scheme, MicroNC- P2, for sharing content among group members, which outperforms state-of-the-art peer-to-peer schemes in our setting. MicroNC-P2 is designed to exploit WiFi overhearing and network coding, based on a local packet broadcast framework, MicroBroadcast, which we developed specifically for Android phones. We evaluate MicroCast on a testbed consisting of seven Android phones, and we show that it brings significant performance benefits without battery penalty.

2012

Modeling and Measuring Performance of Data Dissemination in Opportunistic Networks

Nikodin Ristanovic

In this thesis we focus on understanding, measuring and describing the performance of Opportunistic Networks (ONs) and their applications. An “opportunistic network” is a term introduced to describe a sparse, wireless, ad hoc network with highly mobile nodes. The opportunistic networking paradigm deviates from the traditional end-to-end connectivity concept: Forwarding is based on intermittent connectivity between mobile nodes (typically, users with wireless devices); complete routes between sources and destinations rarely exist. Due to this unique property of spontaneous link establishment, the challenges that exist in ONs are specific. The unstructured nature of these networks makes it difficult to give any performance guarantees on data dissemination. For this reason, in Part I of this thesis we explore the dynamics that affect the performance of opportunistic networks. We choose a number of meaningful scenarios where our models and algorithms can be validated using large and credible data sets. We show that a drift and jump model that takes a spatial approach succeeds in capturing the impact of infrastructure and mobile-to-mobile exchanges on an opportunistic content update system. We describe the effects of these dynamics by using the age distribution of a dynamic piece of data (i.e., information updates) as the performance measure. The model also succeeds in capturing a strong bias in user mobility and reveals the existence of regions, whose statistics play a critical role in the performance perceived in the network. We exploit these findings to design an application for greedy infrastructure placement, which relies on the model approximation for a large number of nodes. Another great challenge of opportunistic networking lies in the fact that the bandwidth available on wireless links, coupled with ad hoc networking, failed to rival the capacity of backbones and to establish opportunistic networks as an alternative to infrastructure-based networks. For this reason, we never study ONs in an isolated context. Instead, we consider the applications that leverage interconnection between opportunistic networks and legacy networks and we study the benefits this synergy brings to both. Following this approach, we use a large operator-provided data set to show that opportunistic networks (based on Wi-Fi) are capable of offloading a significant amount of traffic from 3G networks. At the same time, the offloading algorithms we propose reduce the amount of energy consumed by mobiles, while requiring Wi-Fi coverage that is several times smaller than in the case of real-time offloading. Again we confirm and reuse the fact that user mobility is biased towards certain regions of the network. In Part II of this thesis, we treat another issue that is essential for the acceptance and evolution of opportunistic networks and their applications. Namely, we address the absence of experimental results that would support the findings of simulation based studies. Although the techniques such as contact-based simulations should intuitively be able to capture the performance of opportunistic applications, this intuition has little evidence in practice. For this reason, we design and deploy an experiment with real users who use an opportunistic Twitter application, in a way that allows them to maintain communication with legacy networks (i.e., cellular networks, the Internet). The experiment gives us a unique insight into certain performance aspects that are typically hidden or misinterpreted when the usual evaluation techniques (such as simulation) are used. We show that, due to the commonly ignored factors (such as the limited transmission bandwidth), contact-based simulations significantly overestimate delivery ratio and obtain delays that are several times lower than those experimentally acquired. In addition to this, our results unanimously show that the common practice of assuming infinite cache sizes in simulation studies, leads to a misinterpretation of the effects of a backbone on an opportunistic network. Such simulations typically overestimate the performance of the opportunistic component, while underestimating the utility of the backbone. Given the discovered deficiencies of the contact-based simulations, we consider an alternative statistical treatment of contact traces that uses the weighted contact graph. We show that this approach offers a better interpretation of the impact of a backbone on an opportunistic network and results in a closer match when it comes to modeling certain aspects of performance (namely, delivery ratio). Finally, the security requirements for the opportunistic applications that involve an interconnection with legacy networks are also highly specific. They cannot be fully addressed by the solutions proposed in the context of autonomous opportunistic (or ad hoc) networks, nor by the security frameworks used for securing the applications with continuous connectivity. Thus, in Part III of this thesis, we put together a security framework that fits the networks and applications that we target (i.e., the opportunistic networks and applications with occasional Internet connectivity). We then focus on the impact of security print on network performance and design a scheme for the protection of optimal relaying capacity in an opportunistic multihop network. We fine-tune the parameters of our scheme by using a game-theoretic approach and we demonstrate the substantial performance gains provided by the scheme.

EPFL2012

A framework for network coding in challenged wireless network

David Cavin, Alaeddine El Fawal, Jean-Yves Le Boudec, Yoav Sasson

Network coding is an area that has emerged in 2000, and has since then attracted an increasing interest, as it promises to have a significant impact in both the theory and practice of networks. To evaluate its performance in realistic situation, we developed a network coding based framework for challenged wireless networks where disconnection and reconnection is frequent as in PANs (Personal Area Networks) or vehicular networks, resulting in a new appelation for these scenarios as Delay Tolerant networks (DTN). For living in such hostile environment our development complies with several constraints as portability, flexibility, genericity, etc. Moreover to reduce the development effort using our framework, a single implementation might be used as standalone as well as inside a simulation environment.

2006

Modeling and Measuring Performance of Data Dissemination in Opportunistic Networks

Nikodin Ristanovic

EPFL2012