Smart factories, vehicles, and cities increasingly use wireless rechargeable sensor networks (WRSNs) for communication. A distinct advantage of WRSNs is that they can be placed in remote, inaccessible, or even biologically or chemically contaminated areas for communication, surveillance, and reconnaissance in military and environmental applications. However, the potential of these WRSNs is restricted by their reliance on limited energy sources like batteries, which can impede their smooth functioning.
The primary challenge of WRSNs is to effectively charge and maintain the batteries of the sensors in the network. The charging efficiency plummets as the charging distance increases. Therefore, single charging is more energy-efficient than multicharging as it can charge a sensor node at a closer range. However, when multiple nodes are present, multicharging may achieve higher efficiency.
This motivated a team of researchers led by Professor Sungrae Cho, from the School of Computer Science and Engineering, Chung-Ang University, to optimize mobile charging of sensors efficiently through wireless power transmission technology. As Prof. Cho states, “ The wireless power transmission using a mobile charger was designed to be an efficient method, but if a directional antenna was not used, this method was power inefficient. Therefore, I started researching to see if there is an efficient way to use it. ”
In a recent article published in IEEE Internet of Things Journal , the researchers developed an energy-efficient adaptive directional charging (EEADC) algorithm that considers the density of sensor nodes to adaptively choose single charging or multicharging . As EEADC dynamically determines the charging strategy based on the charging efficiency, the researchers achieved equal or better charging efficiency than single charging and simultaneously reduced energy waste due to overuse of multicharging.
This article was made available online on 6 April 2022 and was published in Volume 9 Issue 19 of the journal on 1 October 2022.
EEADC employs a mean-shift algorithm considering node density to determine single charging/multicharging clusters that is more efficient than the standard K -Means algorithms employed in most Monte Carlo (MC) clustering methods. Each cluster is classified as a single-charging or multicharging cluster according to the number of sensor nodes it contains. The charging strategy, which includes the charging point, beam direction, charging power, and charging time, is then determined according to the type of cluster.
For a multicharging cluster, the non-convex optimization problem having multiple feasible regions led the researchers to employ the discretized charging strategy decision (DCSD) algorithm to solve the problem efficiently. The DCSD divides the problem into two subproblems. The candidate charging points are obtained by solving the first subproblem. Then, DCSD selects the point with the lowest energy consumption among the candidate charging points as the optimal charging point. The researchers used simulations to compare EEADC to conventional charging methods in practice. The team demonstrated that EEADC outperformed the existing methods with respect to power consumption and charging delay by 10% and 9%, respectively.
In summary, the adaptive and directional features of EEADC significantly enhance the energy efficiency of charging sensors in WRSNs. As Prof. Cho explains, “ Using this algorithm, the charging efficiency can be significantly increased by using a directional antenna and a directional beam for charging the sensor node, and sensors located close to each other can be efficiently charged at the same time. ”
Industrial sites such as smart factories, large ships, and construction sites will greatly benefit once this algorithm is employed. Effective and efficient monitoring of diverse sites through a wireless sensor network would be seamlessly achieved through this technology. The energy-efficient mobile charging of the sensors would significantly reduce the maintenance cost of WRSNs.
***
Reference
DOI: https://doi.org/10.1109/JIOT.2022.3163400
Authors: Donghyun Lee 1 , Cheol Lee 2 , Gunhee Jang 3 , Woongsoo Na 4 , and Sungrae Cho 1
Affiliations:
1 School of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea; 2 Naver Corporation ETECH Clound Dev2 Qucell Networks Access S/W Development, Naver Corporation, Seongnam, South Korea; 3 Qucell Networks, Seongnam, South Korea; 4 Department of Computer Science and Engineering, Kongju National University, Cheonan, South Korea;
About Chung-Ang University
Chung-Ang University is a private comprehensive research university located in Seoul, South Korea. It was started as a kindergarten in 1916 and attained university status in 1953. It is fully accredited by the Ministry of Education of Korea. Chung-Ang University conducts research activities under the slogan of “Justice and Truth.” Its new vision for completing 100 years is “The Global Creative Leader.” Chung-Ang University offers undergraduate, postgraduate, and doctoral programs, which encompass a law school, management program, and medical school; it has 16 undergraduate and graduate schools each. Chung-Ang University’s culture and arts programs are considered the best in Korea.
Website: https://neweng.cau.ac.kr/index.do
About Professor Sungrae Cho
Sungrae Cho is a Professor of Computer Science and Engineering at Chung-Ang University . His research focuses on operating power efficient network systems, developing multiple-access technology for next-generation cellular network systems, and development for IRS based communication systems. He received the B.S. and M.S. degrees in electronics engineering from Korea University and Ph.D. in electrical and computer engineering from the Georgia Institute of Technology. Prof. Cho has published over 90 articles, served numerous international conferences as an Organizing Committee Chair, such as IEEE SECON, ICOIN, ICTC, ICUFN, TridentCom, and IEEE MASS, as well as a Program Committee Member for conferences, such as IEEE ICC, MobiApps, SENSORNETS, and WINSYS.
IEEE Internet of Things Journal
Computational simulation/modeling
Not applicable
Energy-Efficient Directional Charging Strategy for Wireless Rechargeable Sensor Networks
1-Oct-2022