Researchers Find Higher Energy Efficacy with a Directional Antenna and Beam for WRSNs

By Chad Cox

Production Editor

Embedded Computing Design

November 23, 2022

News

The need for wireless rechargeable sensor networks (WRSNs) is a must with Smart technologies taking over everything from our homes to our transportation. WSRNs are ideal for military and ecological disaster applications amongst others.

Scholars from Chung-Ang University, Korea, created an energy-efficient adaptive directional charging (EEADC) algorithm that respects the mass of sensor nodes to either select a single charging or multicharging cluster. Professor Sungrae Cho, from the School of Computer Science and Engineering, Chung-Ang University says, “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.”

The EEADC algorithm has been tested to be more economical than K-Means algorithms utilized in most Monte Carlo (MC) clustering processes. This approach contains the charging point, beam direction, charging power, and charging time. Researchers utilized a discretized charging strategy decision (DCSD) algorithm for multicharging clusters to solve the non-convex optimization problem. Divided in subproblems, the charging points are achieved by solving one subproblem as the DCSD chooses which point is running at the lowest power.

For more information, and to read the scholarly article, visit here

Chad Cox is the Production Editor at Embedded Computing Design. His responsibilities are centered around content creation, writing and editing, and article research and development. Chad covers industry news and events and is known to interact with various industrial leaders via on-premise visits and online interviews. He is responsible for the digital footprint and dissemination of news via social media posts, advertising creation and the production of newsletters including the Embedded Computing Design’s Daily.

He is well versed in many facets of industrial computing including Edge AI, IoT, Processing, Security, Open Source, and more.

Chad graduated from the University of Cincinnati with a B.A. in Cultural and Analytical Literature and holds a master’s in education.

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