A General Cross-Layer Cloud Scheduling Framework for Multiple IoT Computer Tasks.

Guanlin Wu, Weidong Bao, Xiaomin Zhu, Xiongtao Zhang

Abstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

An intelligent job scheduling and real-time resource optimization for edge-cloud continuum in next generation networks.Scientific reports · 2025
Article

4 · The record

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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.

Guanlin WuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China. wuguanlin16@nudt.edu.cn.

Weidong BaoCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China. wdbao@nudt.edu.cn.

Xiaomin ZhuCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China. xmzhu@nudt.edu.cn.

Xiongtao ZhangCollege of Systems Engineering, National University of Defense Technology, Changsha 410073, China. zhangxiongtao14@nudt.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diversity of IoT services and applications brings enormous challenges to improving the performance of multiple computer tasks' scheduling in cross-layer cloud computing systems. Unfortunately, the commonly-employed frameworks fail to adapt to the new patterns on the cross-layer cloud. To solve this issue, we design a new computer task scheduling framework for multiple IoT services in cross-layer cloud computing systems. Specifically, we first analyze the features of the cross-layer cloud and computer tasks. Then, we design the scheduling framework based on the analysis and present detailed models to illustrate the procedures of using the framework. With the proposed framework, the IoT services deployed in cross-layer cloud computing systems can dynamically select suitable algorithms and use resources more effectively to finish computer tasks with different objectives. Finally, the algorithms are given based on the framework, and extensive experiments are also given to validate its effectiveness, as well as its superiority.

Indexed as

computer taskcross-layer cloud computinggeneral scheduling frameworkIoT servicesspecific scheduling models and algorithms

Identifiers

PMID29789515

DOI10.3390/s18061671

PMCPMC6022133

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LicenceCC BY

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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.