Abstract
In Internet of Things (IoT), the lifespan of Wireless Sensor Networks (WSN) has often become an issue. Sensor nodes are typically battery powered. However, high energy consumption by Radio Frequency (RF) module limits the lifespan of sensor nodes. In conventional WSN, the frequency of data transmission is normally fixed or adjusted according to requests from the gateway. In this paper, we present a WSN system for intelligent sensing. We propose a low-energy algorithm for sensor data transmission from sensor nodes for such system. In this algorithm, the sensor nodes are able to self-control their data transmission according to the trends of data. We adopt Adaptive Duty Cycle for adjustment of data transmission frequency and Compressive Sensing (CS) for sensor data compression. The simulation results show that Collective Transmission with CS-based data compression achieves 83.34% of RF energy reduction for the best-case transmission and 83.31% of RF energy reduction in the worst-case transmission, compared to the Continuous Transmission.
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016: Green Communications and Networking |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 42-46 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781509038374 |
| DOIs | |
| Publication status | Published - 2016 Dec 7 |
| Event | 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016 - Fez, Morocco Duration: 2016 Oct 26 → 2016 Oct 29 |
Other
| Other | 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016 |
|---|---|
| Country | Morocco |
| City | Fez |
| Period | 16/10/26 → 16/10/29 |
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Keywords
- Intelligent Sensing
- Internet of Things (IoT)
- Low-Energy Algorithm
- Wireless Sensor Networks
ASJC Scopus subject areas
- Computer Networks and Communications
- Communication
Cite this
Low-energy algorithm for self-controlled Wireless Sensor Nodes. / Bin Baharudin, Ahmad Muzaffar; Saari, Mika; Sillberg, Pekka; Rantanen, Petri; Soini, Jari; Kuroda, Tadahiro.
Proceedings - 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016: Green Communications and Networking. Institute of Electrical and Electronics Engineers Inc., 2016. p. 42-46 7777188.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Low-energy algorithm for self-controlled Wireless Sensor Nodes
AU - Bin Baharudin, Ahmad Muzaffar
AU - Saari, Mika
AU - Sillberg, Pekka
AU - Rantanen, Petri
AU - Soini, Jari
AU - Kuroda, Tadahiro
PY - 2016/12/7
Y1 - 2016/12/7
N2 - In Internet of Things (IoT), the lifespan of Wireless Sensor Networks (WSN) has often become an issue. Sensor nodes are typically battery powered. However, high energy consumption by Radio Frequency (RF) module limits the lifespan of sensor nodes. In conventional WSN, the frequency of data transmission is normally fixed or adjusted according to requests from the gateway. In this paper, we present a WSN system for intelligent sensing. We propose a low-energy algorithm for sensor data transmission from sensor nodes for such system. In this algorithm, the sensor nodes are able to self-control their data transmission according to the trends of data. We adopt Adaptive Duty Cycle for adjustment of data transmission frequency and Compressive Sensing (CS) for sensor data compression. The simulation results show that Collective Transmission with CS-based data compression achieves 83.34% of RF energy reduction for the best-case transmission and 83.31% of RF energy reduction in the worst-case transmission, compared to the Continuous Transmission.
AB - In Internet of Things (IoT), the lifespan of Wireless Sensor Networks (WSN) has often become an issue. Sensor nodes are typically battery powered. However, high energy consumption by Radio Frequency (RF) module limits the lifespan of sensor nodes. In conventional WSN, the frequency of data transmission is normally fixed or adjusted according to requests from the gateway. In this paper, we present a WSN system for intelligent sensing. We propose a low-energy algorithm for sensor data transmission from sensor nodes for such system. In this algorithm, the sensor nodes are able to self-control their data transmission according to the trends of data. We adopt Adaptive Duty Cycle for adjustment of data transmission frequency and Compressive Sensing (CS) for sensor data compression. The simulation results show that Collective Transmission with CS-based data compression achieves 83.34% of RF energy reduction for the best-case transmission and 83.31% of RF energy reduction in the worst-case transmission, compared to the Continuous Transmission.
KW - Intelligent Sensing
KW - Internet of Things (IoT)
KW - Low-Energy Algorithm
KW - Wireless Sensor Networks
UR - http://www.scopus.com/inward/record.url?scp=85010298679&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85010298679&partnerID=8YFLogxK
U2 - 10.1109/WINCOM.2016.7777188
DO - 10.1109/WINCOM.2016.7777188
M3 - Conference contribution
AN - SCOPUS:85010298679
SP - 42
EP - 46
BT - Proceedings - 2016 International Conference on Wireless Networks and Mobile Communications, WINCOM 2016: Green Communications and Networking
PB - Institute of Electrical and Electronics Engineers Inc.
ER -