In this paper, the optimal working schemes for wireless sensor networks with multiple base stations and wireless energy transfer devices are proposed. The wireless energy transfer devices also work as data gatherers while charging sensor nodes. The wireless sensor network is firstly divided into sub networks according to the concept of Voronoi diagram. Then, the entire energy replenishing procedure is split into the pre-normal and normal energy replenishing stages. With the objective of maximizing the sojourn time ratio of the wireless energy transfer device, a continuous time optimization problem for the normal energy replenishing cycle is formed according to constraints with which sensor nodes and wireless energy transfer devices should comply. Later on, the continuous time optimization problem is reshaped into a discrete multi-phased optimization problem, which yields the identical optimality. After linearizing it, we obtain a linear programming problem that can be solved efficiently. The working strategies of both sensor nodes and wireless energy transfer devices in the pre-normal replenishing stage are also discussed in this paper. The intensive simulations exhibit the dynamic and cyclic working schemes for the entire energy replenishing procedure. Additionally, a way of eliminating "bottleneck" sensor nodes is also developed in this paper.
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http://dx.doi.org/10.3390/s150306270 | DOI Listing |
Sensors (Basel)
December 2024
School of Electrical and Computer Engineering, National Technical University of Athens, 15772 Athens, Greece.
Sensors (Basel)
December 2024
School of Information Science and Technology, Guangdong University of Foreign Studies, Guangzhou 510420, China.
The major task of a wireless sensor network (WSN) is data collection. Key predistribution (KP) is to establish pairwise keys for secure communication in a WSN, such that all collected data could be securely sent to a backend database. Most research on KP-like schemes is dedicated to enhancing resiliency against node capture attack (NA) and retaining the link connectivity in the meantime.
View Article and Find Full Text PDFPolymers (Basel)
December 2024
Department of Electronic Engineering, Institute for Wearable Convergence Electronics, Kyung Hee University, 1732 Deogyeong-daero, Giheung-gu, Yongin 17104, Republic of Korea.
An energy crisis, resulting from rapid population growth and advancements in the Internet of Things, has increased the importance of energy management strategies. Conventionally, energy management is conducted using sensors; however, additional energy is required to maintain sensor operation within these systems. Herein, an all-fiber-based triboelectric nanogenerator with O plasma treatment, graphene oxide/tannic acid solution coating, and hexane/1-octadecanethiol solution coating (AFT-OGH) is fabricated to implement a self-powered sensor, generating a high electrical power density, of 0.
View Article and Find Full Text PDFNano Lett
January 2025
School of Advanced Materials, Shenzhen Graduate School, Peking University, Shenzhen 518055, P. R. China.
The high responsivity and broad spectral sensitivity of organic photodetectors (OPDs) present a bright future of commercialization. However, the relatively high dark current density still limits its development. Herein, two novel nonpolar p-type conjugated small molecules, NSN and NSSN, are synthesized as interface layers to enhance the performance of the OPDs, which not only can tune energy alignments and increase the reverse charge injection barrier but also can reduce the interfacial trap density.
View Article and Find Full Text PDFBiomed Microdevices
January 2025
Department of Electrical and Computer Engineering, Rutgers University, Piscataway, NJ, 08854, USA.
Wearable and implantable biosensors have rapidly entered the fields of health and biomedicine to diagnose diseases and physiological monitoring. The use of wired medical devices causes surgical complications, which can occur when wires break, become infected, generate electrical noise, and are incompatible with implantable applications. In contrast, wireless power transfer is ideal for biosensing applications since it does not necessitate direct connections between measurement tools and sensing systems, enabling remote use of the biosensors.
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