Information Centric Networking in the IoT Experiments with NDN in - - PowerPoint PPT Presentation

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Information Centric Networking in the IoT Experiments with NDN in - - PowerPoint PPT Presentation

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Information Centric Networking in the IoT Experiments with NDN in the Wild Emmanuel Baccelli 1 , Christian Mehlis 3 , Oliver Hahm 1 , Thomas C. Schmidt 2 , Matthias Whlisch 3 INRIA 1 HAW Hamburg 2 Freie Universitt Berlin 3 ACM ICN 2014

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Information Centric Networking in the IoT Experiments with NDN in the Wild

Emmanuel Baccelli1, Christian Mehlis3, Oliver Hahm1, Thomas C. Schmidt2, Matthias Wählisch3 INRIA1 HAW Hamburg2 Freie Universität Berlin3

ACM ICN 2014 Paris, September 2014

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The Beauty of ICN in the IoT

  • Simplified, natural API
  • Example: Get “/paris/cordeliers/

amphi_farabeuf/temperature”

  • Increased robustness by caching
  • Lossy wireless links in the IoT
  • Ease data fusion by hop-wise

replication

  • Reduced network layer
  • Inherent auto-configuration
  • IoT devices w/o user interface

ACM ICN 2014 Paris, September 2014

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The Ugly of ICN in the IoT

Additional states

  • Constrained devices are prevalent in the IoT

Long names

  • IoT link layer technologies usually support short MTUs

Do the benefits outweigh the challenges of ICN in the IoT?

ACM ICN 2014 Paris, September 2014

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What is this Talk About?

  • Explore basic feasibility and tradeoffs of ICN in the IoT
  • Report about experiments in real world testbed
  • Propose interoperable ICN enhancements for the IoT

ACM ICN 2014 Paris, September 2014

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Agenda  IoT Model  A Priori Challenges  Enable ICN in the IoT  Experiments  Summary

ACM ICN 2014 Paris, September 2014

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IoT Model in this Talk

Constrained devices

  • Power consumption in mWatt compared to Watt
  • Computations in megaFLOPS compared to GigaFLOPS
  • Memory in Kilobytes compared to Gigabytes

Multi-hop wireless communication

  • MTUs between 30 bytes and 40 bytes

Standardized interconnection

  • Connect with Internet-devices

 We look on the very low end IoT devices

in the global (future) Internet!

ACM ICN 2014 Paris, September 2014

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Challenge: Limited Memory

Implications on caching capabilities

  • Small-sized content doable
  • Example: Temperature value 12 bytes => 85 sensor values
  • Medium-sized content requires distributed chunk caching

Implications on overlay applicability

  • ICN should work directly on link-layer

Implications on routing approaches

  • Constant routing states preferred
  • Minimal control traffic

ACM ICN 2014 Paris, September 2014

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Implementing ICN in the IoT: Network Stack

Which ICN implementation?

  • NDN (before the CCN/NDN split ;)

Which operating system for IoT?

  • RIOT

Porting CCN-Lite to RIOT

  • 1,000 lines of C code
  • Required ROM 16 kBytes
  • Required RAM 5 kBytes

ACM ICN 2014 Paris, September 2014

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Basic Routing with Vanilla Interest Flooding (VIF)

Idea

  • Flood all content interests

Advantages

  • Does not rely on additional control traffic
  • Requires no additional states

Disadvantages

  • Does not scale with many nodes
  • Network transmissions are costly in terms of energy

ACM ICN 2014 Paris, September 2014

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Optimized Routing with Reactive Optimistic Name-based Routing (RONR)

Idea

  • Assumption: Whole piece of content is stored on a node
  • Flood only the first interest for a content name
  • Subsequent interests for chunks are unicast

Advantages

  • Reduces the number of radio transmissions, saves energy
  • Still, no control traffic and minimal states

Disadvantage

  • Content delivery can be delayed

ACM ICN 2014 Paris, September 2014

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Experimental Setup

  • Deployment of ICN/IoT implementation in the FU testbed
  • 60 nodes distributed in several rooms and floors
  • Each node with CC1100 radio chip, CPU 868 MHz
  • Maximum link layer frame size 64 bytes
  • Basic configuration of the experiments
  • Size of name length 12 bytes
  • Consider single and multi consumer scenarios
  • Consider ICN with and without caching
  • Chunk size set to 58 bytes
  • Content size aligned to prevent fragmentation

ACM ICN 2014 Paris, September 2014

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Results - Single Consumer Scenario

  • It worked!
  • Relatively large interest

signaling overhead

  • 50% less radio transmissions

compared to Vanilla flooding

  • In particular, less broadcasts

ACM ICN 2014 Paris, September 2014

Vanilla Interest Flooding Reactive Opportunistic Forwarding

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Results - Multi Consumer Scenario for RONR

  • Scales almost linearly with the

number of consumers

  • Cache accommodates 20 chunks
  • 2% of 96 kBytes of RAM
  • 50% less radio transmissions
  • Unicast benefits from caching

ACM ICN 2014 Paris, September 2014

Without Caching With Caching

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Comparison with Common IoT Protocols

  • Common IETF protocol suite for IoT: 6LoWPAN + RPL
  • Comparing required memory for protocol stack

 ICN requires 70% less ROM, and 80% less RAM

We now perform the same multi-consumer experiment with caching.

ACM ICN 2014 Paris, September 2014

Module ROM RAM RPL + 6LoWPAN ~52 kBytes ~27 kBytes CCN-Lite ~16 kBytes ~5 kBytes

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RONR Compared with 6LoWPAN/RPL Stack

ACM ICN 2014 Paris, September 2014

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Summary & Outlook

We started from very basic scenarios and simple mechanisms

  • ICN is applicable in the Internet of Things
  • NDN/CCN implementation available with low memory footprint
  • Caching and opportunistic forwarding help

to reduce packet loss and energy consumption

  • ICN may outperform current IoT protocols

In the future

  • Deal better with typically small frame sizes
  • Header compression and fragmentation layer below NDN
  • IoT-specific content replication and cache replacement
  • Additional communication models
  • Short naming schemes optimized for constrained devices

ACM ICN 2014 Paris, September 2014

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Let’s Rock IoT with ICN!

  • Download, extend, and

experiment

  • http://github.com/RIOT-

OS/RIOT

  • http://www.riot-os.org
  • Over 2,700 wireless sensor

nodes across six sites

  • RIOT and thus ICN runs in

IoT-LAB

  • Open for external researchers

ACM ICN 2014 Paris, September 2014