Maximizing energy efficiency in off-peak hours: A novel sleep scheme for WLAN access points

Oh, Hyeontaek; Newaz, S. H. Shah; Park, Sang‐Don; Choi, Jun Kyun

doi:10.1109/noms.2016.7502830

Cited by 6 publications

(3 citation statements)

References 15 publications

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“…A particular case occurred at 14:00 h when the energy savings with the two strategies were the same. It was remarkable that while we applied our method to APs, SWs, and R, other methods like Oh et al (2016) could only force the APs to sleep. Thus, our method can be applied to more devices in the network in an integral way.…”

Section: Discussionmentioning

confidence: 99%

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A novel energy-saving method for campus wired and dense WiFi network applying machine learning and idle cycling techniques

Alvarado,

Suárez

2024

FACETS

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University campus networks need wired (ethernet) and dense wireless fidelity networks that have devices like access points, switches, and routers that are always turned on. Consequently, they generate two important problems: the energy bill and the influence of carbon dioxide into the atmosphere. Energy savings are the solution to those problems. There are several proposals to augment the energy savings separately in ethernet and wireless fidelity, but there is no integrated method to simultaneously reduce them in both parts of the networks. Our novel method combines idle cycling and machine learning techniques to efficiently obtain energy savings in both parts of the network simultaneously. We categorize network devices into two groups: (a) those that are always turned on and (b) those that can be dynamically turned on or off based on network performance. We formulated two algorithms that decide when to turn on and off access points. We use Ward's machine learning hierarchical clustering technique to optimize the energy savings of our model in the network of the Unidades Tecnológicas de Santander (Bucaramanga, Colombia). We showed that energy savings of 21.5 kWh per day are possible. The success of the model in this context highlights its potential to achieve substantial energy savings.

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Section: Discussionmentioning

confidence: 99%

“…Active sleeping of APs, SWs, and Rs is a traditional technique. For example, Oh et al (2016) force APs to sleep to save energy on a WiFi network. Two techniques in switched networks to reduce power consumption during idle time intervals are used in Manjate et al (2018).…”

Section: Related Workmentioning

confidence: 99%

A novel energy-saving method for campus wired and dense WiFi network applying machine learning and idle cycling techniques

Alvarado,

Suárez

2024

FACETS

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“…In efforts to reduce traffic and enhance power efficiency during off-peak hours, [30] proposed a solution determining the optimal sleep interval duration for access points. This approach balanced delay requirements with energy efficiency through innovative algorithms.…”

Section: B Congestion Controlmentioning

confidence: 99%

Optimizing the Over and Underutilization of Network Resources During Peak and Off-Peak Hours

Badshah,

Daud,

Khan

et al. 2024

IEEE Access

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In 2022, the digital population reached 5.4 billion, leading to network congestion, primarily attributed to the widespread use of social media, robotic programs, and prime-time television during peak hours. This congestion posed a significant challenge, as sensitive services struggled to operate effectively during peak hours, while network resources remained largely underutilized during off-peak hours. To tackle this issue, we propose the implementation of Regional Servers. These servers are designed to initially store less critical data during peak hours and subsequently transfer it to the cloud during off-peak hours, effectively optimizing network resources. The results demonstrate that the deployment of regional servers proved highly efficient in mitigating delays and reducing jitters that users typically experience during peak hours, successfully addressing the challenges posed by network congestion.

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A Green Converged TWDM-PON and 5G HetNet Catering Applications Demanding Low Latency

Mohammed

Newaz

Sankar

et al. 2020

Optical Fiber Technology

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Maximizing energy efficiency in off-peak hours: A novel sleep scheme for WLAN access points

Cited by 6 publications

References 15 publications

A novel energy-saving method for campus wired and dense WiFi network applying machine learning and idle cycling techniques

A novel energy-saving method for campus wired and dense WiFi network applying machine learning and idle cycling techniques

Optimizing the Over and Underutilization of Network Resources During Peak and Off-Peak Hours

A Green Converged TWDM-PON and 5G HetNet Catering Applications Demanding Low Latency

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