Balanced Distribution Strategy for the Number of Recharging Requests Based on Dynamic Dual-Thresholds in WRSNs

Bian, Xiaojie (författare): School of Computer Science, Software and Cyberspace Security, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China

Sha, Chao (författare): School of Computer Science, Software and Cyberspace Security, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China

Malekian, Reza, 1983- (författare): Malmö universitet,Institutionen för datavetenskap och medieteknik (DVMT),Internet of Things and People (IOTAP)

Zhao, Chuanxin (författare): School of Computer and Information, Anhui Normal University, Wuhu, Anhui, China

Wang, Ruchuan (författare): School of Computer Science, Software and Cyberspace Security, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China

(creator_code:org_t)

2024
2024
Engelska.
Ingår i: IEEE Internet of Things Journal. - : Institute of Electrical and Electronics Engineers (IEEE). - 2327-4662.

Relaterad länk:: https://urn.kb.se/re...; visa fler...; https://doi.org/10.1...; visa färre...

Abstract Ämnesord

Stäng

“Request Triggered Recharging” has been a flexible type of scheduling schemes to allow the Mobile Charging Vehicle (MCV) to supply energy for sensor nodes on demand. However, in most existing works, MCV always passively waits for the arrival of the unpredictable requests that may cause it missing the best departure time to serve nodes. To solve this problem, we propose a Balanced Distribution strategy for the number of Recharging Requests based on dynamic dual-thresholds (BDRR). Firstly, the adjustable Double Recharging Request Thresholds (DRRTs) are set for each node to ensure that all the requesting nodes can be successfully charged. Then, the Method for Setting the Energy Replenishment Value (MSERV) is proposed to enable the distribution of the moments at which nodes send out their recharging requests being concentrated within each period. Furthermore, an efficient traversal path for the MCV is constructed by safe or dangerous scheduling strategy, and the Charging Capacity Reduction Scheme (CCRS) is also executed to help survive more nodes in need. Finally, a Passer-by Recharging Scheme (PRS) is introduced to further improve the energy efficiency of the MCV. Simulation results show that BDRR outperforms the compared algorithms in terms of surviving rate of sensors as well as the energy efficiency of MCV with different network scales.

Av författaren/redakt...: Bian, Xiaojie; Sha, Chao; Malekian, Reza, ...; Zhao, Chuanxin; Wang, Ruchuan

Om ämnet

TEKNIK OCH TEKNOLOGIER: TEKNIK OCH TEKNO ...; och Elektroteknik oc ...; och Kommunikationssy ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.