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A Compression Algorithm Design and Simulation for Processing Large Volumes of Data from Wireless Sensor Networks

Priyanka Vangali, Xiaokun Yang. Published in Wireless.

Communications on Applied Electronics
Year of Publication: 2017
Publisher: Foundation of Computer Science (FCS), NY, USA
Authors: Priyanka Vangali, Xiaokun Yang
10.5120/cae2017652650

Priyanka Vangali and Xiaokun Yang. A Compression Algorithm Design and Simulation for Processing Large Volumes of Data from Wireless Sensor Networks. Communications on Applied Electronics 7(4):1-5, July 2017. BibTeX

@article{10.5120/cae2017652650,
	author = {Priyanka Vangali and Xiaokun Yang},
	title = {A Compression Algorithm Design and Simulation for Processing Large Volumes of Data from Wireless Sensor Networks},
	journal = {Communications on Applied Electronics},
	issue_date = {July 2017},
	volume = {7},
	number = {4},
	month = {Jul},
	year = {2017},
	issn = {2394-4714},
	pages = {1-5},
	numpages = {5},
	url = {http://www.caeaccess.org/archives/volume7/number4/745-2017652650},
	doi = {10.5120/cae2017652650},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

As Internet of things (IoT) advances, the growth in data volume from wireless sensor networks (WSNs) is explosive and is likely to overwhelm traditional datacenters. Therefore this paper presents a field-programmable gate array (FPGA) design and simulation on a data compression algorithm as a case study. By collecting and compressing raw data from IoT network, the large amount of sensor data is dramatically reduced and translated into valuable information to the servers. Simulation results show that the compression ratio can reach 30.08% with a very low processing latency (20 ms for compressing 1 KB sensor data).

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Keywords

Data compression, Field-programmable gate array (FPGA), Internet of things (IoT), Wireless Sensor Networks (WSNs)