D2D assisted cooperative computational offloading strategy in edge cloud computing networks Article Swipe
Yanyan Wang
,
Dechuan Kong
,
Haojie Chai
,
Han Qiu
,
Rui Xue
,
Shuhang Li
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-96719-8
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1038/s41598-025-96719-8
In the computational offloading problem of edge cloud computing (ECC), almost all researches develop the offloading strategy by optimizing the user cost, but most of them only consider the delay and energy consumption, and seldom consider the task waiting delay. This is very unfavorable for tasks with high sensitive latency requirements in the current era of intelligence. In this paper, by using D2D (Device-to-Device) technology, we propose a D2D-assisted collaboration computational offloading strategy (D-CCO) based on user cost optimization to obtain the offloading decision and the number of tasks that can be offloaded. Specifically, we first build a task queue system with multiple local devices, peer devices and edge processors, and compare the execution performance of computing tasks on different devices, taking into account user costs such as task delay, power consumption, and wait delay. Then, the stochastic optimization algorithm and the back-pressure algorithm are used to develop the offloading strategy, which ensures the stability of the system and reduces the computing cost to the greatest extent, so as to obtain the optimal offloading decision. In addition, the stability of the proposed algorithm is analyzed theoretically, that is, the upper bounds of all queues in the system are derived. The simulation results show the stability of the proposed algorithm, and demonstrate that the D-CCO algorithm is superior to other alternatives. Compared with other algorithms, this algorithm can effectively reduce the user cost.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1038/s41598-025-96719-8
- https://www.nature.com/articles/s41598-025-96719-8.pdf
- OA Status
- gold
- Cited By
- 2
- References
- 22
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4409332804
All OpenAlex metadata
Raw OpenAlex JSON
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https://openalex.org/W4409332804Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1038/s41598-025-96719-8Digital Object Identifier
- Title
-
D2D assisted cooperative computational offloading strategy in edge cloud computing networksWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-04-10Full publication date if available
- Authors
-
Yanyan Wang, Dechuan Kong, Haojie Chai, Han Qiu, Rui Xue, Shuhang LiList of authors in order
- Landing page
-
https://doi.org/10.1038/s41598-025-96719-8Publisher landing page
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-
https://www.nature.com/articles/s41598-025-96719-8.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://www.nature.com/articles/s41598-025-96719-8.pdfDirect OA link when available
- Concepts
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Computer science, Cloud computing, Enhanced Data Rates for GSM Evolution, Edge computing, Distributed computing, Computer network, Artificial intelligence, Operating systemTop concepts (fields/topics) attached by OpenAlex
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2Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2Per-year citation counts (last 5 years)
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22Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_location.pdf_url | https://www.nature.com/articles/s41598-025-96719-8.pdf |
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| primary_location.raw_source_name | Scientific Reports |
| primary_location.landing_page_url | https://doi.org/10.1038/s41598-025-96719-8 |
| publication_date | 2025-04-10 |
| publication_year | 2025 |
| referenced_works | https://openalex.org/W1560887569, https://openalex.org/W4391508368, https://openalex.org/W4308292990, https://openalex.org/W4308427276, https://openalex.org/W4229083998, https://openalex.org/W4392296615, https://openalex.org/W4285220735, https://openalex.org/W3188272948, https://openalex.org/W4322503617, https://openalex.org/W4402137150, https://openalex.org/W4221046147, https://openalex.org/W4291033374, https://openalex.org/W4301852635, https://openalex.org/W2967528593, https://openalex.org/W4210590066, https://openalex.org/W4226428948, https://openalex.org/W4313549926, https://openalex.org/W3209954252, https://openalex.org/W4200006375, https://openalex.org/W2116175219, https://openalex.org/W2956717547, https://openalex.org/W2005647218 |
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