Lossless Data Compression for Energy Efficient Transmission

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Details

Wireless networks are very fast replacing the traditional wired networking for the small and long distance area. With the rapid expansion in the data generation in the digital world and need for information sharing between the different stakeholders / collaborative members for business and scientific needs, today the volume of data being transmitted is also facing exponential growth. Wireless transmission of a single bit can require over 1000 times more energy than a single 32-bit computation. It can therefore be beneficial to perform additional computation to reduce the number of bits transmitted. If the energy required to compress data is less than the energy required to send it, there is a net energy savings and an increase in battery life for portable computers. This paper proposes energy savings possible by losslessly compressing data prior to transmission. The proposed work focuses that, with several typical compression algorithms, there is actually a net energy increase when compression is applied before transmission. Reasons for this increase are explained and proposal will be to avoid it.

Autorentext

Author did his B.Tech from Kurukshetra University, in 2003 and M.E from Panjab University,Chandigarh(India) in 2009 with Honors and having an experience of around 10 years. At present he is pursuing his PhD from Thapar University,Patiala. He is having number of research papers(National/International) level and M.Tech guidance on his name.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783659221682
    • Sprache Englisch
    • Größe H220mm x B220mm x T150mm
    • Jahr 2012
    • EAN 9783659221682
    • Format Kartonierter Einband (Kt)
    • ISBN 978-3-659-22168-2
    • Titel Lossless Data Compression for Energy Efficient Transmission
    • Autor Saurabh Mittal
    • Untertitel This book compares various data compression algorithms and analyses their performance for energy efficient transmission
    • Herausgeber LAP Lambert Academic Publishing
    • Anzahl Seiten 132
    • Genre Informatik

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