WebIDE Cloud Server Resource Allocation With Task Pre-Scheduling in IoT Application Development Article Swipe
Huaijun Wang
,
Junhuai Li
,
Jubo Tian
,
Kan Wang
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/access.2020.2967790
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1109/access.2020.2967790
WebIDE is leveraged for IoT application development, which could adapt to the rapid growth of IoT applications and meanwhile facilitate the rapid development. Resource allocation is of vital significance in the WebIDE cloud service system. Existing resource allocation approaches may encounter issues such as unbalanced resource assignments, which could lead to the reduced system resource utilization or extended system response time. Existing methods are typically on the basis of predetermined resource demands for each task, and not applicable to the case that the resource demands are dynamic and unknown. This article predicts the tasks to be performed by the WebIDE cloud service through task pre-scheduling, and then applies the existing resource allocation methods. Firstly, all tasks are classified, based on the execution state, execution operations and WebIDE cloud server resource requirements. Secondly, the grouped tasks are mapped to different system states, with the Markov state transition probability matrix leveraged to model the transition probability between tasks, followed by the prediction model constructed. Finally, integrating task pre-scheduling with ant colony algorithm, WebIDE cloud server resource allocation is carried out. Experiment results show that adding the task prediction model could significantly not only reduce the task response time, but also improve the cloud server resource utilization.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2020.2967790
- https://ieeexplore.ieee.org/ielx7/6287639/8948470/08963672.pdf
- OA Status
- gold
- Cited By
- 7
- References
- 27
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W3002772778
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W3002772778Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/access.2020.2967790Digital Object Identifier
- Title
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WebIDE Cloud Server Resource Allocation With Task Pre-Scheduling in IoT Application DevelopmentWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-01Full publication date if available
- Authors
-
Huaijun Wang, Junhuai Li, Jubo Tian, Kan WangList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2020.2967790Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/8948470/08963672.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/8948470/08963672.pdfDirect OA link when available
- Concepts
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Computer science, Cloud computing, Scheduling (production processes), Internet of Things, Distributed computing, Task (project management), Server, Cloud server, Computer network, Operating system, Embedded system, Management, Economics, Operations managementTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2023: 3, 2021: 2, 2020: 1Per-year citation counts (last 5 years)
- References (count)
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27Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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