Research on the Cloud Acceleration Method for the Compressed Sensing Algorithm under the Internet of Things

DOI

10.2991/meita-15.2015.190How to use a DOI?

Keywords

Internet of Things; Cloud Acceleration; Compressed Sensing; Sparse Representation; Mathematical Optimization; Cloud Computing; Hardware Deployment.

Abstract

In this paper, we conduct research on the cloud acceleration method for the compressed sensing algorithm under the environment of Internet of Things. On the Internet of things perception layer, an important part of the sensor network have been put forward a lot of security mechanisms. Now about access control for sensor networks is a closed network and IOT perception layer will have multiple sensor subnet and mobile users frequently switch between each sensor subnet. Traditional information sampling is based on the Shannon sampling theorem, it is pointed out that the sampling rate of the signal is not less than twice the highest frequency and the signal can be accurate reconstruction. The traditional sampling theorem is an important theoretical base for guidance on how to sample. Through the experimental simulation, the result proves the feasibility and effectiveness of the propose methodology. In the future, we plan to conduct more corresponding research to modify the current approach.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wenzhun Huang
AU  - Shanwen Zhang
PY  - 2015/08
DA  - 2015/08
TI  - Research on the Cloud Acceleration Method for the Compressed Sensing Algorithm under the Internet of Things
BT  - Proceedings of the 2015 International Conference on Materials Engineering and Information Technology Applications
PB  - Atlantis Press
SP  - 1005
EP  - 1010
SN  - 2352-5401
UR  - https://doi.org/10.2991/meita-15.2015.190
DO  - 10.2991/meita-15.2015.190
ID  - Huang2015/08
ER  -