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Le Wang MASTER THESIS PRESENTATION. Evaluation of Compression for Energy-aware Communication in Wireless Networks. Master Thesis Presentation. Supervisor: Professor Jukka Manner Instructor: Sebastian Siikavirta Department of Communications and Networks

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le wang master thesis presentation

Le WangMASTER THESIS PRESENTATION

Evaluation of Compression for Energy-aware Communication in Wireless Networks

master thesis presentation
Master Thesis Presentation
  • Supervisor: Professor Jukka Manner
  • Instructor: Sebastian Siikavirta
  • Department of Communications and Networks
  • Faculty of Electronics, Communications, and Automation
  • Helsinki University of Technology
  • 25th, May, 2009
introduction
Introduction
  • This study aims to investigate the usages of data compression to reduce the energy consumption in a hand-held device.
  • By conducting experiments as the methodologies, the impacts of transmission on energy consumption are explored on wireless interfaces.
  • 9 lossless compression algorithms are examined on popular Internet traffic in the view of compression ratio, speed and consumed energy.
  • Energy consumption of uplink, downlink and overall system is investigated to achieve a comprehensive understanding of compression in wireless networks.
why is it needed
Why is it needed
  • Energy Consumption
    • ICT infrastructure total: power consumption 2.1 TWh

-2.3% of all power consumption in Finland

    • ICT user terminals total: power consumption 4.6 TWh

-5.1% of all power consumption in Finland

  • Greenhouse gas emissions
    • ICT contribution to Greenhouse Gas emission: 2.5% = 1.0 GtCO2eq
    • Mobile user energy consumption is approximate 29kWh = 55 kgco2eq
  • Battery
    • UMTS, HSDPA, IEEE802.11b/g and Bluetooth
    • Camera, GPS, music, movies

EFORE Oy,2008

why is it needed1
Why is it needed
  • Economics

EFORE Oy,2008

motivation
Motivation
  • Energy consumed on a single bit transmission over wireless is over 1000 times greater than a single 32-bit CPU computation
  • Compression reduces file sizes
  • Trade-off between computation and communication
problems
Problems
  • David Salomon-” Data compression is popular for two reasons:
    • (1) People like to accumulate data and hate to throw anything away. No matter how big a storage device one has, sooner or later it is going to overflow. Data compression seems useful because it delays this inevitability.
    • (2) People hate to wait a long time for data transfers.”
  • Data compression is not energy-oriented.
  • Blind or unconditional compressions for energy-aware communication related to wireless networks may result in wasting of energy and even slowing down transmission rate.
compression
Compression
  • Lossy compression is one where compressing data and then decompressing it retrieves data that may well be different from the original
    • G.711, G.726 and AMR
    • WMA and MP3
    • JPEG and PGF
    • MPEG, H.261, H.263 and H.264
  • Lossless compression is in contrast to represent information which can be recovered into the original data without any mismatch.
    • Text compression
compression algorithms
Compression algorithms
  • Statistical compression
    • Huffman Coding, Arithmetic Coding
  • Dictionary Compression
    • Static Dictionary, Adaptive Dictionary
  • Predictive Compression
    • prediction with partial matching, Burrows-Wheeler transform and context mixing
methodology
Methodology
  • Experiment setup
results transmission impact
RESULTS: Transmission Impact

Packet Sizes (UDP)

Sending

Receiving

results transmission impact1
RESULTS: Transmission Impact

Transmission Rate(UDP)

Sending

Receiving

results compression impact
RESULTS: Compression Impact

Hard-to-compress files

results compression impact1
RESULTS: Compression Impact

Hard-to-compress files

Energy required to compress and send JPG, MP3, WMA and EXE files

results compression impact2
RESULTS: Compression Impact

Hard-to-compress files

Energy required to receive and decompress JPG, MP3, WMA and EXE files

results compression impact3
RESULTS: Compression Impact

Hard-to-compress files

Total energy required to transmit JPG, MP3, WMA and EXE files

results compression impact4
RESULTS: Compression Impact

The best ratio/time of the compression programs and the corresponding ratio

results compression impact5
RESULTS: Compression Impact

Easy-to-compress files

Energy required to send BIN, HTML, BMP and XML files

results compression impact6
RESULTS: Compression Impact

Easy-to-compress files

Energy required to receiveBIN, HTML, BMP and XML files

results compression impact7
RESULTS: Compression Impact

Easy-to-compree files

Total energy required to transmit BIN, HTML, BMP and XML files

results compression impact8
RESULTS: Compression Impact

Compressible files

Energy required to compress and send PDF and SWF files

results compression impact9
RESULTS: Compression Impact

Compressible files

Energy required to receive and decompress PDF and SWF files

results compression impact10
RESULTS: Compression Impact

Compressible files

Total energy required to transmit PDF and SWF files

conclusions
Conclusions
  • Hard-to-compress files <-> Direct sending

-JPG, MP3, EXE and WMA

  • Easy-to-compress files <-> Compressing first

-BIN, HTML, BMP and XML

  • Compressible files <-> Depending on circumstance

-PDF and SWF

  • Generic compression programs providing great energy savings.

-gzip, lzma and lzo

  • Energy saving with proper usage of compression in wireless networks

-Uplink: ~57%

-Downlink: ~50%

-Overall: ~50%

future study
Future Study
  • Energy efficiency-driven transmission
    • Other compression algorithms and programs
    • Other traffic, wireless interface behavior
    • Energy consumption of 3G devices
    • Modeling energy consumption of compression
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