Evidence map›Paper›PMID 38067784›Full record

ArticleSensors (Basel, Switzerland)2023

Energy Consumption Minimization in Unmanned Aerial Vehicle-Enabled Secure Wireless Sensor Networks.

Xufei Ding, Wen Tian, Guangjie Liu, Xiaopeng Ji

Open access · goldAbstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
1.5field-weighted citation impact, top 11% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Xufei DingSchool of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Wen TianSchool of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Guangjie LiuSchool of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
Xiaopeng JiSchool of Electronics and Information Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.ORCID 0000-0001-6094-4626
Nanjing University of Information Science and Technology · CN

Funding

Jiangsu Province Natural Science Foundation BK20230415National Key R&D Program of China 2021QY0700National Natural Science Foundation of China U21B2003,62072250Natural Science Foundation of the Jiangsu Higher Education Institutions of China 23KJB120007
6 · The paper itself

Abstract

In wireless sensor networks (WSNs), unmanned aerial vehicles (UAVs) are considered an effective data collection tool. In this paper, we investigate the energy-efficient data collection problem in a UAV-enabled secure WSN without knowing the instantaneous channel state information of the eavesdropper (Eve). Specifically, the UAV collected the information from all the wireless sensors at the scheduled time and forward it to the fusion center while Eve tries to eavesdrop on this confidential information from the UAV. To surmount this intractable and convoluted mixed-integer non-convex problem, we propose an efficient iterative optimization algorithm using the block coordinate descent (BCD) method to minimize the maximum energy consumption of the ground sensor nodes (GSNs) under the constraints of secrecy outage probability (SOP), connection outage probability (COP), minimum secure data, information causality, and UAV trajectory. Numerical results demonstrate the superiority of the algorithm we proposed in energy consumption and secrecy rate compared with other schemes.

Indexed as

data collectionenergy minimizationtrajectory optimizationunmanned aerial vehicle (UAV)wireless sensor network (WSN)

Identifiers

PMID38067784
PMCPMC10708811
OpenAlexW4389056779

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.