Edge assisted, forecast integrated ensemble learning based service management scheme for delay minimization in smart cities applications Article Swipe
K. Hemant Kumar Reddy
,
Rajat Shubhra Goswami
,
Diptendu Sinha Roy
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101806
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.1016/j.jksuci.2023.101806
As the Internet of Things (IoT) is maturing as a technology, innovative and cross-domain IoT applications have seen smart cities being conceived and designed across the globe, though with data and resource management challenges, Quality of Service (QoS) fulfilment challenges among others. These could also be addressed by means of context-aware fog computing at the edge of the network and also by incorporating intelligence at the network edge. Since workload at fog nodes can anytime see sudden changes in demand, hence load migration among fog nodes becomes viable. However, improper migration can lead to further migrations, eventually decreasing performance. In this paper, we present a multi-channel queuing model based smart distributed service management approach and an intelligent resource-aware forecasting technique to predict the required context and resource management. The scheme accomplishes live migration by a resource-aware ensemble forecast method that used current and predicted resource utilization and their context availabilities to address the delay requirement for cross-domain IoT applications. The proposed management algorithms are simulated using CloudSim simulator and the efficacy of the obtained results confirm the superiority of the proposed methods.
Related Topics
Concepts
Computer science
Context (archaeology)
Quality of service
Enhanced Data Rates for GSM Evolution
Workload
Resource allocation
Resource management (computing)
Distributed computing
Service (business)
Edge computing
Domain (mathematical analysis)
Resource (disambiguation)
Computer network
Real-time computing
Artificial intelligence
Economics
Biology
Paleontology
Economy
Mathematical analysis
Operating system
Mathematics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jksuci.2023.101806
- OA Status
- hybrid
- Cited By
- 1
- References
- 43
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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- OpenAlex ID
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https://openalex.org/W4387911330Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.jksuci.2023.101806Digital Object Identifier
- Title
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Edge assisted, forecast integrated ensemble learning based service management scheme for delay minimization in smart cities applicationsWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2023Year of publication
- Publication date
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2023-10-24Full publication date if available
- Authors
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K. Hemant Kumar Reddy, Rajat Shubhra Goswami, Diptendu Sinha RoyList of authors in order
- Landing page
-
https://doi.org/10.1016/j.jksuci.2023.101806Publisher landing page
- Open access
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.jksuci.2023.101806Direct OA link when available
- Concepts
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Computer science, Context (archaeology), Quality of service, Enhanced Data Rates for GSM Evolution, Workload, Resource allocation, Resource management (computing), Distributed computing, Service (business), Edge computing, Domain (mathematical analysis), Resource (disambiguation), Computer network, Real-time computing, Artificial intelligence, Economics, Biology, Paleontology, Economy, Mathematical analysis, Operating system, MathematicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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1Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1Per-year citation counts (last 5 years)
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43Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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