Leaner and Meaner: Network Coding in SIMD enabled Commercial Devices

Research output: Research - peer-reviewArticle in proceeding

Abstract

Although random linear network coding (RLNC) constitutes a highly efficient and distributed approach to enhance communication networks and distributed storage, it requires additional processing to be carried out in the network and in end devices. For mobile devices, this processing translates into energy use that may reduce the battery life of a device. This paper focuses not only on providing a comprehensive measurement study of the energy cost of RLNC in eight different computing platforms, but also explores novel approaches (e.g., tunable sparse network coding) and hardware optimizations for Single Instruction Multiple Data (SIMD) available in the latest generations of Intel and Advanced RISC Machines (ARM) processors. Our measurement results show that the former provides gains of two- to six-fold from the underlying algorithms over RLNC, while the latter provides gains for all schemes from 2x to as high as 20x. Finally, our results show that the latest generation of mobile processors reduce dramatically the energy per bit consumed for carrying out network coding operations compared to previous generations, thus making network coding a viable technology for the upcoming 5G communication systems, even without dedicated hardware.
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Although random linear network coding (RLNC) constitutes a highly efficient and distributed approach to enhance communication networks and distributed storage, it requires additional processing to be carried out in the network and in end devices. For mobile devices, this processing translates into energy use that may reduce the battery life of a device. This paper focuses not only on providing a comprehensive measurement study of the energy cost of RLNC in eight different computing platforms, but also explores novel approaches (e.g., tunable sparse network coding) and hardware optimizations for Single Instruction Multiple Data (SIMD) available in the latest generations of Intel and Advanced RISC Machines (ARM) processors. Our measurement results show that the former provides gains of two- to six-fold from the underlying algorithms over RLNC, while the latter provides gains for all schemes from 2x to as high as 20x. Finally, our results show that the latest generation of mobile processors reduce dramatically the energy per bit consumed for carrying out network coding operations compared to previous generations, thus making network coding a viable technology for the upcoming 5G communication systems, even without dedicated hardware.
Original languageEnglish
Title of host publicationWireless Communications and Networking Conference (WCNC), 2016 IEEE
Number of pages6
PublisherIEEE
Publication date2016
ISBN (Electronic)978-1-4673-9814-5
DOI
StatePublished - 2016
Publication categoryResearch
Peer-reviewedYes
EventIEEE Wireless Communications and Networking Conference - Doha, Qatar
Duration: 3 Apr 20166 Apr 2016

Conference

ConferenceIEEE Wireless Communications and Networking Conference
LandQatar
ByDoha
Periode03/04/201606/04/2016
SeriesI E E E Wireless Communications and Networking Conference. Proceedings
ISSN1525-3511
ID: 242497842