A Predictive Logistic Regression Based Doze Mode Energy-Efficiency Mechanism in EPON Article Swipe
MohammadAmin LOTFOLAHI
,
Cheng‐Zen Yang
,
I‐Shyan Hwang
,
AliAkbar Nikoukar
,
Yuhua Wu
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2017edp7350
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1587/transinf.2017edp7350
Ethernet passive optical network (EPON) is one of the energy-efficient access networks. Many studies have been done to reach maximum energy saving in the EPON. However, it is a trade-off between achieving maximum energy saving and guaranteeing QoS. In this paper, a predictive doze mode mechanism in an enhanced EPON architecture is proposed to achieve energy saving by using a logistic regression (LR) model. The optical line terminal (OLT) in the EPON employs an enhanced Doze Manager practicing the LR model to predict the doze periods of the optical network units (ONUs). The doze periods are estimated more accurately based on the historical high-priority traffic information, and logistic regression DBA (LR-DBA) performs dynamic bandwidth allocation accordingly. The proposed LR-DBA mechanism is compared with a scheme without energy saving (IPACT) and another scheme with energy saving (GDBA). Simulation results show that LR-DBA effectively improves the power consumption of ONUs in most cases, and the improvement can be up to 45% while it guarantees the QoS metrics, such as the high-priority traffic delay and jitter.
Related Topics
Concepts
Computer science
Jitter
Dynamic bandwidth allocation
Quality of service
Energy (signal processing)
Real-time computing
Energy consumption
Bandwidth (computing)
Efficient energy use
Logistic regression
Ethernet
Scheme (mathematics)
Computer network
Telecommunications
Statistics
Machine learning
Engineering
Mathematical analysis
Mathematics
Electrical engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1587/transinf.2017edp7350
- https://www.jstage.jst.go.jp/article/transinf/E101.D/3/E101.D_2017EDP7350/_pdf
- OA Status
- diamond
- Cited By
- 4
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2789333465
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2789333465Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1587/transinf.2017edp7350Digital Object Identifier
- Title
-
A Predictive Logistic Regression Based Doze Mode Energy-Efficiency Mechanism in EPONWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-01-01Full publication date if available
- Authors
-
MohammadAmin LOTFOLAHI, Cheng‐Zen Yang, I‐Shyan Hwang, AliAkbar Nikoukar, Yuhua WuList of authors in order
- Landing page
-
https://doi.org/10.1587/transinf.2017edp7350Publisher landing page
- PDF URL
-
https://www.jstage.jst.go.jp/article/transinf/E101.D/3/E101.D_2017EDP7350/_pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://www.jstage.jst.go.jp/article/transinf/E101.D/3/E101.D_2017EDP7350/_pdfDirect OA link when available
- Concepts
-
Computer science, Jitter, Dynamic bandwidth allocation, Quality of service, Energy (signal processing), Real-time computing, Energy consumption, Bandwidth (computing), Efficient energy use, Logistic regression, Ethernet, Scheme (mathematics), Computer network, Telecommunications, Statistics, Machine learning, Engineering, Mathematical analysis, Mathematics, Electrical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
4Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 2, 2022: 1, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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