Evidence map›Paper›PMID 31146376›Full record

ArticleSensors (Basel, Switzerland)2019

Time-Efficient Allocation Mechanisms for Crowdsensing Tasks with Precedence Constraints.

Xiaocan Wu, Yu-E Sun, He Huang, Yang Du, Danlei Huang

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2019. 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
–field-weighted citation impact
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.

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

5 authors.

Xiaocan WuThe School of Computer Science and Technology, Soochow University, Suzhou 215006, China. 20184227017@stu.suda.edu.cn.
Yu-E SunThe School of Rail Transportation, Soochow University, Suzhou 215131, China. sunye12@suda.edu.cn.
He HuangThe School of Computer Science and Technology, Soochow University, Suzhou 215006, China. huangh@suda.edu.cn.ORCID 0000-0003-2768-6607
Yang DuThe Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou 215123, China. jannr@mail.ustc.edu.cn.
Danlei HuangThe School of Computer Science and Technology, Soochow University, Suzhou 215006, China. 20185227048@stu.suda.edu.cn.

Funding

National Natural Science Foundation of China No. 61572342, No. 61672369Natural Science Foundation of Jiangsu Province No. BK20161258
6 · The paper itself

Abstract

Crowdsensing has emerged as an efficient and inexpensive way to perform specialized tasks by leveraging external crowds. In some crowdsensing systems, different tasks may have different requirements, and there may be precedence constraints among them, such as the Unmanned Aerial Vehicle (UAV) crowdsensing systems. Moreover, minimizing the total execution time is a regular target for finishing the crowdsensing tasks with precedence constraints. As far as we know, only a few existing studies consider the precedence constraints among crowdsensing tasks, and none of them can minimize the total execution time simultaneously. To tackle this challenge, an efficient allocation mechanism for tasks with precedence constraints is first proposed, which can minimize the total execution time. Then, a case study is given to show how to fit our mechanism in the UAV crowdsensing system. Finally, the simulation results show that the proposed mechanisms have good approximate optimal ratios under different parameter settings and are efficient for the UAV crowdsensing system as well.

Indexed as

crowdsensingexecution time minimizationprecedence constrainttask allocationUAV

Identifiers

PMID31146376
PMCPMC6603554

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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.