ArticleSensors (Basel, Switzerland)2022
Transmission Power Control in Wireless Sensor Networks Using Fuzzy Adaptive Data Rate.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Innovative DMHS Algorithm Application in Wireless Sensor Networks for Efficient Routing in High-Risk Environments.Sensors (Basel, Switzerland) · 2023Article
- Distributed Consensus Kalman Filter Design with Dual Energy-Saving Strategy: Event-Triggered Schedule and Topological Transformation.Sensors (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the technology of Internet of Things (IoT) becomes popular, the number of sensor nodes also increases. The network coverage, extensibility, and reliability are also the key points of technical development. To address the challenge of environmental restriction and deployment cost, most sensor nodes are powered by batteries. Therefore, the low-power consumption becomes an important issue because of the finite value of battery capacity. In addition, significant interference occurs in the environment, thereby complicating reliable wireless communication. This study proposes a fuzzy-based adaptive data rate for the transmission power control in wireless sensor networks to balance the communication quality and power consumption. The error count and error interval perform the inputs of a fuzzy system and the corresponding fuzzy system output is guard that is utilized for limiting the upper bounds of data rate and transmission power. The long-term experimental results are introduced to demonstrate that the control algorithm can overcome environmental interference and obtain low-power performance. The sensor nodes have reliable communication under an ultra-low-power consumption. The experimental results show that the total power consumption of the proposed approach has been improved 73% compared with the system without executing the algorithm and also indicate the Packet Error Rate (PER) is close to 1%. Therefore, the proposed method is suitable for the battery supply IoT system.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.