Dunking the data center

Cutler, Ben; Fowers, Spencer G.; Kramer, Jeffrey A.; Peterson, Eric

doi:10.1109/mspec.2017.7864753

Cited by 44 publications

(18 citation statements)

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“…For example, image processing operations can be performed collaboratively or offloaded to surface-based infrastructure. Indeed, in the near future it may be possible for AUVs to link with data centers that are located on the surface [14].…”

Section: Power and Operational Timementioning

confidence: 99%

Toward Large-Scale Autonomous Marine Pollution Monitoring

Flores

Motlagh

Zuniga

et al. 2021

IEEE Internet Things M.

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Marine pollution is a growing worldwide concern, affecting the health of marine ecosystems, human health, and weather patterns. To reduce underwater pollution, it is critical to have access to accurate information about the extent of marine pollutants as otherwise appropriate countermeasures and cleaning measures cannot be chosen. Currently such information is difficult to acquire as existing monitoring solutions are highly laborious or costly, limited to specific pollutants, and have limited spatial and temporal resolution. In this article, we present a research vision of large-scale autonomous marine pollution monitoring that uses coordinated groups of autonomous underwater vehicles (AUV)s to monitor the extent and characteristics of marine pollutants. We highlight key requirements and reference technologies to establish a research roadmap for realizing this vision. We also address the feasibility of our vision, carrying out controlled experiments that address classification of pollutants and collaborative underwater processing, two key research challenges for our vision. Index Terms-AUV; Underwater drones; Marine pollution monitoring; Autonomous robots; Sensing Coordinated Movement and Processing: Besides coordinating sampling areas, AUVs should coordinate their movements to ensure they remain in each other's communication range. Coordinated movement also offers additional benefits, such as the potential for using collaborative sensing or processing strategies for improving the recognition of pollutants.

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Section: Power and Operational Timementioning

confidence: 99%

Toward Large-Scale Autonomous Marine Pollution Monitoring

Flores

Motlagh

Zuniga

et al. 2021

IEEE Internet Things M.

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“…ϓ 2 = 1 1 + 5 5 (7) In formulating the latency, this paper considers the Age of Information metric. The age of information measures the time elapsed since the last received update was generated at the source [38].…”

Section: )mentioning

confidence: 99%

“…This has led to the use of renewable energy in data centres [5][6]. The cooling costs can be reduced by changing data centre location to alternative locations such as the ocean [7][8][9]. The use of underwater data centres is unsuitable for geographical locations with insufficient maritime resources.…”

Section: Introductionmentioning

confidence: 99%

Sustainable cloud computing for cognitive intent based networks

Periola¹,

Obayiuwana²

2021

Nig. J. Tech.

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Intent based networks enable auto-configuration and require low latency access to cloud platforms. The use of cloud platforms incurs high operational costs. Low latency access can be realized by siting data centres close to subscribers. This paper proposes aquaria data centers with low operating costs and latency. In LTE, cloud platforms are normally accessed via the packet network gateway reachable via the serving gateway and mobility management entity. Aquaria data centers are sited close to LTE subscribers and accessed via the mobility management entity. This reduces the size of control packets in the LTE network. Simulations show that the proposed architecture reduces the size of control packets by up to 49.7% and 99.3% when header packets are uncompressed and compressed respectively. The delay associated with receiving configuration information is reduced by 50% on average. The channelcapacity is enhanced by up to 22.8% on average. Keywords: Data centers, LTE-Advanced, Peak Age of Information, Channel Capacity, Header (Control) Packet

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“…The alternative is to immerse a complete rack or data center itself, possibly with conventional air-based heat transfer into the surrounding liquid. An undersea approach based on this has been announced by Microsoft [18].…”

Section: B Building Levelmentioning

confidence: 99%

Data Center Challenges and Their Power Electronics

Krein

2017

CPSS TPEA

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Abstract-Data centers use more than 1.5% of all electricity in China and the U.S., with continuing growth. This paper reviews the power hierarchy levels within modern data centers. It considers energy consumption and power electronics challenges across all levels of a data center, including building distribution, dc architectures, and conversion down to the board level. Power electronics plays a central role throughout the hierarchy, and emerging approaches are described. Strategies that enhance center energy efficiency, both in terms of overall center operation and in terms of computation performance, are discussed.Index Terms-Data centers, dc distribution, dc-dc converters, server racks, power utilization factor, dc power architecture, digital power.

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Dunking the data center

Cited by 44 publications

References 0 publications

Toward Large-Scale Autonomous Marine Pollution Monitoring

Toward Large-Scale Autonomous Marine Pollution Monitoring

Sustainable cloud computing for cognitive intent based networks

Data Center Challenges and Their Power Electronics

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