APRS: adaptive real-time payload data reduction scheme for IoT/WSN sensor board with multivariate sensors

被引：7

作者：

Alduais, N. A. M. ^{[1
]}

Abdullah, J. ^{[1
]}

Jamil, A. ^{[1
]}

机构：

[1] Univ Tun Hussein Onn Malaysia UTHM, Fac Elect & Elect Engn FKEE, Wireless & Radio Sci Ctr WARAS, Batu Pahat, Johor, Malaysia

来源：

INTERNATIONAL JOURNAL OF SENSOR NETWORKS | 2018年 / 28卷 / 04期

关键词：

WSN; wireless sensor network; IoT; internet of things; multivariate data; accuracy; energy consumption; data reduction; PRINCIPAL COMPONENT ANALYSIS; MIMO DECISION FUSION; PERFORMANCE ANALYSIS; ENERGY DETECTION; WIRELESS; NETWORKS; COMPRESSION; PREDICTION; MODEL;

D O I：

10.1504/IJSNET.2018.096458

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a new simple mechanism called as adaptive real-time payload data reduction scheme (APRS) for energy efficiency purpose is proposed. APRS aims to reduce the transmitted packet size for each sensed payload, moreover it prevents any transmissions if no significant change is reported by the payload sensing block. Performance of APRS was evaluated through simulation by utilising various real-time datasets. In addition, APRS was successfully implemented in testbed. In conclusion, APRS has managed to show its simplicity and flexibility for the real-time IoT/WSN application when it is compared with the other algorithms and its reduction ratio during a transmission is within acceptable range of 81-94%. The average of the total percentage of energy saved by applied APRS in all nodes is 95%. Overall, APRS has high performance in the reduction ratio of data and efficiency in energy consumption when it is compared with other recent multivariate data reduction methods.

引用

页码：211 / 229

页数：19

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