TY - JOUR
T1 - Intelligent Charging Path Planning for IoT Network over Blockchain-Based Edge Architecture
AU - Cho, Hsin Hung
AU - Wu, Hsin Te
AU - Lai, Chin Feng
AU - Shih, Timothy K.
AU - Tseng, Fan Hsun
N1 - Funding Information:
Manuscript received March 23, 2020; revised July 11, 2020 and August 24, 2020; accepted September 22, 2020. Date of publication September 29, 2020; date of current version February 4, 2021. This work was supported in part by the Young Scholar Fellowship Program by Ministry of Science and Technology (MOST) in Taiwan, under Grant MOST109-2636-E-003-001, and in part by the MOST in Taiwan, under Grant MOST108-2221-E-197-012-MY3. (Corresponding author: Fan-Hsun Tseng.) Hsin-Hung Cho and Hsin-Te Wu are with the Department of Computer Science and Information Engineering, National Ilan University, Yilan 26047, Taiwan (e-mail: hhcho@niu.edu.tw; hsinte@niu.edu.tw).
Publisher Copyright:
© 2014 IEEE.
PY - 2021/2/15
Y1 - 2021/2/15
N2 - A wireless rechargeable sensor network was proposed to extend the lifetime of the wireless sensor network. In this article, a charger is combined together with a self-propelled vehicle to provide a more flexible result of charger deployment. The dynamic chargers path selection problem is defined and mapped into the traveling salesman problem. Four metaheuristic algorithms for Internet-of-Things (IoT) applications are designed, and the higher fitness value between the charging path and the number of dead IoT devices is achieved. However, metaheuristic approaches may spend more time on searching solutions so that many IoT devices overuse limited power and fail to be charged for a long time, leading to power exhaustion. In this article, the edge computing technique is applied to accelerate the obtainment of charging paths with the well-defined edge/centralized unit switching. Moreover, to assure the calculated path trustworthy and will not be tampered with, the blockchain technology is adopted. The proposed architecture maintains high-level information credibility while transmitting the information of charging paths within the cloud and edge. The simulation results showed that the proposed method is capable of achieving better charging efficiency and less deployment cost.
AB - A wireless rechargeable sensor network was proposed to extend the lifetime of the wireless sensor network. In this article, a charger is combined together with a self-propelled vehicle to provide a more flexible result of charger deployment. The dynamic chargers path selection problem is defined and mapped into the traveling salesman problem. Four metaheuristic algorithms for Internet-of-Things (IoT) applications are designed, and the higher fitness value between the charging path and the number of dead IoT devices is achieved. However, metaheuristic approaches may spend more time on searching solutions so that many IoT devices overuse limited power and fail to be charged for a long time, leading to power exhaustion. In this article, the edge computing technique is applied to accelerate the obtainment of charging paths with the well-defined edge/centralized unit switching. Moreover, to assure the calculated path trustworthy and will not be tampered with, the blockchain technology is adopted. The proposed architecture maintains high-level information credibility while transmitting the information of charging paths within the cloud and edge. The simulation results showed that the proposed method is capable of achieving better charging efficiency and less deployment cost.
UR - http://www.scopus.com/inward/record.url?scp=85100750908&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85100750908&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2020.3027418
DO - 10.1109/JIOT.2020.3027418
M3 - Article
AN - SCOPUS:85100750908
VL - 8
SP - 2379
EP - 2394
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
SN - 2327-4662
IS - 4
M1 - 9208679
ER -