Chain-routing scheme with compressive sensing-based data acquisition for Internet of Things-based wireless sensor networks

被引:8
|
作者
Aziz, Ahmed [1 ,2 ]
Osamy, Walid [1 ]
Khedr, Ahmed M. [3 ,4 ]
Salim, Ahmed [4 ,5 ]
机构
[1] Univ Benha, Fac Comp & Artificial Intelligence, Comp Sci Dept, Banha, Egypt
[2] Sharda Univ, Fac Engn & Technol, Andijon City, Uzbekistan
[3] Univ Sharjah, Comp Sci Dept, Sharjah 27272, U Arab Emirates
[4] Zagazig Univ, Math Dept, Fac Sci, Zagazig, Egypt
[5] Qassim Univ, Dept Comp Sci, Coll Arts & Sci, Al Mithnab, Saudi Arabia
关键词
SIGNAL RECOVERY; PROTOCOL; RECONSTRUCTION;
D O I
10.1049/ntw2.12002
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The emerging Internet of Things (IoT)-based systems that integrate diverse types of sensors, mobiles and other technologies to physical world is becoming increasingly popular for use in wide varieties of applications. Compressive sensing (CS)-based information acquisition and in-network compression provide an effective method for accurate data recovery at the base station (BS) with reduced cost of communication. In this study, how CS can be combined with routing protocols for gathering data in IoT-based Wireless Sensor Networks (WSNs) in an energy-efficient manner are examined. A novel chain-routing scheme with CS based data acquisition is introduced that includes the following new algorithms: (1) Seed Estimation Algorithm (SEA) to find the best measurement matrix by selecting the best-estimated seed, (2) Chain Construction Algorithm (CCA) to organise the network nodes during transmitting and receiving process, (3) Compression approach with reduced consumption of energy that improves the lifetime of the network by minimising the local data traffic, and (4) Reconstruction Algorithm (RA) that reconstructs the original data with minimum reconstruction error. Here, extensive simulation and analysis results prove the performance of our proposed method in improving the network lifetime 35% better than the ECST algorithm and 93% better than the PEGASIS algorithm. In addition, the proposed reconstruction algorithm exceeds the other reconstruction algorithms performance.
引用
收藏
页码:43 / 58
页数:16
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