Optimizing Task Offloading for Power Line Inspection in Smart Grid Networks with Edge Computing: A Game Theory Approach Article Swipe
Lu Xu
,
Sihan Yuan
,
Zhongyuan Nian Zhongyuan Nian
,
Chunfang Mu
,
Xi Li
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/info15080441
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/info15080441
In the power grid, inspection robots enhance operational efficiency and safety by inspecting power lines for information sharing and interaction. Edge computing improves computational efficiency by positioning resources close to the data source, supporting real-time fault detection and line monitoring. However, large data volumes and high latency pose challenges. Existing offloading strategies often neglect task divisibility and priority, resulting in low efficiency and poor system performance. This paper constructs a power grid inspection offloading scenario using Python 3.11.2 to study and improve various offloading strategies. Implementing a game-theory-based distributed computation offloading strategy, simulation analysis reveals issues with high latency and low resource utilization. To address these, an improved game-theory-based strategy is proposed, optimizing task allocation and priority settings. By integrating local and edge computing resources, resource utilization is enhanced, and latency is significantly reduced. Simulations show that the improved strategy lowers communication latency, enhances system performance, and increases resource utilization in the power grid inspection context, offering valuable insights for related research.
Related Topics
Concepts
Computer science
Enhanced Data Rates for GSM Evolution
Edge computing
Task (project management)
Line (geometry)
Distributed computing
Grid
Game theory
Smart grid
Power grid
Mobile edge computing
Power (physics)
Artificial intelligence
Electrical engineering
Engineering
Mathematics
Quantum mechanics
Geometry
Physics
Systems engineering
Mathematical economics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/info15080441
- OA Status
- gold
- Cited By
- 2
- References
- 14
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W4401074036Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/info15080441Digital Object Identifier
- Title
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Optimizing Task Offloading for Power Line Inspection in Smart Grid Networks with Edge Computing: A Game Theory ApproachWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-07-29Full publication date if available
- Authors
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Lu Xu, Sihan Yuan, Zhongyuan Nian Zhongyuan Nian, Chunfang Mu, Xi LiList of authors in order
- Landing page
-
https://doi.org/10.3390/info15080441Publisher landing page
- 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://doi.org/10.3390/info15080441Direct OA link when available
- Concepts
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Computer science, Enhanced Data Rates for GSM Evolution, Edge computing, Task (project management), Line (geometry), Distributed computing, Grid, Game theory, Smart grid, Power grid, Mobile edge computing, Power (physics), Artificial intelligence, Electrical engineering, Engineering, Mathematics, Quantum mechanics, Geometry, Physics, Systems engineering, Mathematical economicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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2Total citation count in OpenAlex
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2025: 1, 2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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