ACM ICN 2020, Montreal, Canada
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7th ACM Conference on Information-Centric Networking (ICN 2020)

Half-day Tutorial: Practical NDN Application Development and Seamless Deployment

Overview

Preliminary Tutorial Program

  • Tuesday, September 29, 2020, Zoom

  • 12pm - 3pm EDT: Half-day Tutorial: Practical NDN Application Development and Seamless Deployment

  • (15 minutes)

    "Warm up: Review of NDN 101

    Alex Afanasyev

    • We start the tutorial with a quick overview of the basic NDN concepts, together with pointers to the existing codebase and resources for developers and users, followed by a roadmap of the tutorial.

       

  • (25 minutes)

    Pub-Sub in NDN-Lite

    Tianyuan Yu

    • NDN-Lite is a framework to enable end user-controlled home IoT systems over NDN. This talk describes how NDN-Lite realizes home IoT apps via a pub-sub API, and embeds the security support under it, saving application developers not only from directly dealing with Interest-Data exchanges but also from directly handling cryptographic operation details needed for the system security and user privacy.

       

  • (25 minutes)

    npChat as an Illustrative App Examples

    Lan Wang

    • npChat, a peer-to-peer social networking app, will be intro- duced as a simple application example to illustrate the use of pub-sub and common name API in application develop- ment. Earlier we use NDN-Lite framework to highlight how pub-sub can be leveraged to simplify system software imple- mentation with security embedded into the API support. In this application example we show how npChat application, based on exchange of semantically named and secured data, can operate in ad hoc scenarios.

       

  • (20 minutes)

    Namespace-Focused APIs for NDN: NDN-CNL, NTSchema

    Jeff Burke

    • We present an introduction to the NDN Common Name API and available libraries and their APIs. This set of libraries include the supporting functions developed for consumer- producer exchanges. We will use a specific example tp illustrate how various functions, including security and synchronization mechanics, can be realized using simple high-level routines.

       

  • NDN CNL Example

    Xinyu Ma

  • 10 minutes: Coffee Break

  • (25 minutes)

    Plug-n-Play of NDN Applications

    John (Hunter) Dellaverson

    • Given NDN offers desired properties such as securing data directly, removal of dependency on addresses, and support for asynchronous communication, one would belief conduct- ing NDN trials at edges should be simple. In reality, however, attempting to run NDN apps on even a small number of nodes faces considerable setup steps. Previous experience from IP operations tends to influence the focus on establishing connectivity among NDN nodes, however NDN must also configure names and security parameters – what are the relations between the configurations of different pieces, and what must be done first?
      In this last part of the tutorial, we argue that a new entity needs to be plugged into its running environment to enable it to play. We show that the fundamentally different networking models of IP and NDN leads to their different configurations. We explain what NDN configuration opera- tions must be done “out-of-band” and what can be automated, and how to enable NDN plug-n-play by developing tools to ease configuration and to automate reachability discovery.

       

  • (15 minutes)

    Self-learning in NDN: Enabling an Auto-configured NFD

    Teng Liang

    • We made two observations on deploying or demonstrating NDN applications at edge. First, to run NDN applications between neighboring nodes requires non-trivial network configuration, which includes manually creating Face for connectivity and adding name-based routes. Moreover, these configurations require the knowledge of peer addresses. Second, the forwarding behaviors for edge networks are not specified, which provides little support for applications. These two observations motivate our work of self-learning in NDN, which enables an auto-configured NFD. In this part, we first introduce how self-learning works, which enables NFD with data discovery, automatic Face and routes setup, smart Interest forwarding, and better NACK handling. Then, we use a hands-on demonstration to show how self-learning enables plug-n-play NFD.

       

  • (40 minutes)

    Q & A

    • In addition to addressing questions in real time during the tutorial, we also plan to set up an online board to collect questions from the audience that are touch broader scope or deserve deeper elaborations, to be covered in this dedicated Q & A session. This session will also offer the audience opportunities to share their work related to NDN API development and configuration solutions.

       

Introduction

With its built-in security and ad hoc mobility support, Named Data Networking (NDN) offers an ideal substrate to meet the needs of emerging new applications, and NDN trials should meet the least resistance at edges. This tutorial is to share our recent progress on new API and plug-n-play support which address the following two obstacles in experimentation with NDN:

  • Limited high-level APIs to explore new application ideas, forcing users to work with low level Interest-Data exchange and reimplement basic mechanics (e.g., reliable data fetching); and

  • Complexity in deploying NDN applications in local NDN environments, be it an NDN island connected to the NDN testbed, small-scale local NDN testbed, or an ad hoc NDN environment.

The new API is built by combining the results from existing work, which have been published in recent ICN conferences, namely consumer/producer API, Common Name Library (CNL), and pub-sub support. The plug-n-play support is based on our deepened understanding about the relations between NDN configuration and reachability, and the tools to make the former a turn-key solution and the latter automated.

In this tutorial we start with a quick overview of NDN development, followed by a combination of pilot application and the API library descriptions, and wrap up with NDN plug-n-play discussions and demonstrations.

Tutorial Description

This short tutorial is expected to run 3 hours including a 20-minute break. It will be mostly real-time presentations with a few pieces of recorded demonstrations.

While NDN brings the concept of fetching data using names via Interest/Data packet exchange at the network level, application developers do not need to directly work with such low-level details. Over the last few years, several application/developer-friendly high-level APIs have been proposed that hide data fetching specifics while providing NDN security and other functionality such as multi-party synchronization. In particular, developers can use consumer/producer API support and publish-subscribe concepts to leverage NDN mechanics without directly dealing with individual Interest and Data packets. Moreover, given the major focus on naming in NDN, the team developed an approach to structure application development around the name strucure—NDN Common Name Library (CNL). With CNL, an application can explore available (discoverable) namespaces, subscribe to a namespace branch (i.e., subscribe to a topic) as well as publish data. Therefore, one goal of this tutorial is to introduce high-level concepts such as pub-sub and CNL API that developers can use to write NDN applications. We note that the consumer/producer API work, complements the CNL API by providing data transport services beneath the namespace.

Presenters

  • Alex Afanasyev

    Florida International University

    • Alex Afanasyev is an Assistant Professor in Florida International University, Miami. He received his Ph.D. degree in computer science from UCLA in 2013. His research focus is on the next-generation Internet architecture as part of the Named Data Networking (NDN) project. His research interests include a variety of topics that are vital for the success of NDN, including scalability of name-based routing, autoconfiguration, distributed data synchronization, application and network security. Dr. Afanasyev is also leading the development effort of the overall NDN codebase.

       

  • Lan Wang

    University of Memphis

    • Lan Wang is Professor and Chair of the Computer Science Department at the University of Memphis. She holds a B.S. degree (1997) in Computer Science from Peking University, China and a Ph.D. degree (2004) in Computer Science from University of California, Los Angeles. Her research interests include future Internet architecture, Internet routing, network security, network performance measurement and sensor networks.

       

  • Beichuan Zhang

    University of Arizona

    • Beichuan Zhang is an Associate Professor at the Department of Computer Science, the University of Arizona. His research interest is in Internet routing architectures and protocols. He has been working on Named Data Networking, green networking, and inter-domain routing. He received the Applied Networking Research Prize in 2011 by ISOC and IRTF, and best paper awards at IEEE ICDCS in 2005 and IWQoS in 2014. Dr. Zhang received Ph.D. from UCLA and B.S. from Peking University.

       

  • Jeff Burke

    UCLA/REMAP

    • Jeff Burke is Professor In-Residence and Associate Dean forTechnology and Innovation at the UCLA School of Theater,Film and Television (TFT), where he has been a faculty member since 2001. His research explores the intersections ofthe built environment, computer networks, and storytelling. Burke co-founded REMAP, a joint center of TFT and the Henry Samueli School of Engineering and Applied Science,which uses a mixture of research, artistic production, and community engagement to investigate the interrelationships among culture, community, and technology. He is Co-PI and application team lead for the Named Data Networking research project.

       

  • Tianyuan Yu

    UCLA

    • Tianyuan Yu is a Ph.D. student in the Computer Science Department of UCLA, under the supervision of Prof. Lixia Zhang. His main research interests are Named Data Networking, Internet of Things and Network Security. He is also contributing to the development of the NDN software.

       

  • Xinyu Ma

    UCLA

    • Xinyu Ma is a Ph.D candidate in the Computer Science Department of UCLA, under the supervision of Prof. Lixia Zhang. His research focus is applications and algorithms in Named Data Networking (NDN). He is the main maintainer of python-ndn, an NDN client library in Python 3. He is also contributing to the development of NDN IoT.

       

  • Hunter Dellaverson

    UCLA

    • Hunter Dellaverson is a Ph.D student in the Computer Science Department of UCLA, under the supervision of Prof. Lixia Zhang. His main research interests are Named Data Networking, network security, and usable security.

       

  • Teng Liang

    Peng Cheng Lab

    • Teng Liang is an Assistant Researcher at Peng Cheng Lab. Dr. Liang received his Ph.D. degree in computer science from the University of Arizona in 2020. His research focus is on next-generation Internet architecture as part of the Named Data Networking (NDN) project. His research interests include NDN forwarding, deployment and applications.

       

  • Lixia Zhang

    UCLA

    • Lixia Zhang is a Professor in the Computer Science Department of UCLA. She received her Ph.D in computer science from MIT and was a member of the research staff at Xerox PARC before joining UCLA. She is a fellow of ACM and IEEE, the recipient of IEEE Internet Award, and the holder of UCLA Postel Chair in Computer Science. Since 2010 she has been leading the effort on the design and development of the NDN architecture.