Power efficiency of thin clients

Vereecken, Willem; Deboosere, Lien; Simoens, Pieter; Vermeulen, Brecht; Colle, Didier; Develder, Chris; Pickavet, Mario; Dhoedt, Bart; Demeester, Piet

doi:10.1002/ett.1431

Cited by 13 publications

(8 citation statements)

References 17 publications

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“…However, as noted in Section 2, the amount of time spent in putting the link to sleep and waking it up consumes significant power close to P active , but it was accounted as P idle in Equation (2). Indeed, the amount of time (thus power) spent in waking up and putting into sleep the link may constitute a substantial portion of the total time.…”

Section: A Second Estimate Of Power Consumption: Considering T W and T Smentioning

confidence: 99%

Study of the potential energy savings in Ethernet by combining Energy Efficient Ethernet and Adaptive Link Rate

Reviriego

Maestro

Hernández

et al. 2011

Trans. Emerging Tel. Tech.

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Abstract:The Energy Efficient Ethernet (EEE) standard (IEEE 802.3az) has introduced some modifications to existing Ethernet standards with the aim of improving energy efficiency in the transmission of data frames. The adopted mechanism is to use different power modes of operation such that a device can be put into a low-power mode when there is no data to transmit and awake it very quickly upon frame arrival. This is expected to reduce energy consumption significantly, especially on low-loaded links. An alternative to EEE, known as Adaptive Link Rate (ALR), was also proposed to improve energy effi-ciency in Ethernet by dynamically changing the link speed at different traffic loads. ALR reduces the energy consumption because the lower the link speed, the less energy is consumed. However, this option is no longer considered in the EEE standard process.In this work, the potential energy savings of combining both EEE and ALR are explored. The results show that such a combination can further improve the already efficient EEE standard given the different power overheads associated with transitions between the active and idle power modes at different link speeds. This conclusion provides a clear motivation to investigate the combination of EEE and ALR more in detail in further developments.

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Section: A Second Estimate Of Power Consumption: Considering T W and T Smentioning

confidence: 99%

Study of the potential energy savings in Ethernet by combining Energy Efficient Ethernet and Adaptive Link Rate

Reviriego

Maestro

Hernández

et al. 2011

Trans. Emerging Tel. Tech.

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“…first is at home, latter in a datacenter) permits to consider mobility of tasks and placement of them to reduce the overall power consumption without loosing QoS from user point of view [20]. In comparison to our approach, this model does not consider exotic hardware resources (e.g., webcams, Bluetooth) that some tasks may require and are locals resources.…”

Section: Related Workmentioning

confidence: 99%

Energy-driven consolidation in digital home

Druilhe

Anne

Pulou

et al. 2013

Proceedings of the 28th Annual ACM Symposium on Applied Computing

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As our society becomes more and more digital, the corresponding demand for electric energy is increasing. Despite the power efficient design of devices, this rising trend of energy consumption does not weaken because of more and more devices used in our daily life. Collaboration strategies between devices can reduce their overall electrical consumption. Consolidation -i.e., migrating tasks among devices to place into low power state or to switch off a maximum of unused devices -is a mean of optimizing the consumption of a group of devices. So far, consolidation is mainly used in datacenters. Here, we propose a model to extend this approach to Digital Home. This model takes into account properties, such as the unforeseeable appearance of devices or restrictions due to task nature. Its implementation in a Digital Home environment saves around 25% of the energy consumption in a scenario based on the daily life of a family of four persons.

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“…Conversely increased processing power and range of equipment utilised has resulted in predictions that small power will continue to have a significant impact (Jenkins, Singh & Eames, 2009) and that energy consumption associated with office eqiupment will continue to grow globally in the near future. (Webber et al 2001& Vereecken et al 2010 As noted by Junnila (2007) few studies have focused on quantifying the enduser influence on energy consumption, furthermore most energy managers believe end users influence to be minimal (Lukas, 2000). However it has previously been established that energy use of desktop equipment is highly influenced by occupant behaviour and is flexible in nature (Zhang, Siebers & Aickelin, 2011).…”

Section: Introductionmentioning

confidence: 99%