NUTS scheduling approach for cloud data centers to optimize energy consumption

Sanjeevi, P.; Viswanathan, Pragasam

doi:10.1007/s00607-017-0559-4

Cited by 13 publications

(10 citation statements)

References 31 publications

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“…Finally the posterior distributions are estimated numerically using the NUTS 58 algorithm. This algorithm also calculates the normalization factor p(d) or the probability of the data.…”

Section: Chemical Shift Prediction From the MD Resultsmentioning

confidence: 99%

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

Pérez-Conesa

Keeler

Zhang

et al. 2020

Preprint

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As the first potassium channel with a X-ray structure determined, and given its homol- ogy to eukaryotic channels, the pH-gated prokaryotic channel KcsA has been extensively studied. Nevertheless, questions related in particular to the allosteric coupling between its gates remain open. The many currently available X-ray crystallography structures appear to correspond to various stages of activation and inactivation, offering insights into the molecular basis of these mechanisms. Since these studies have required mutations, com- plexation with antibodies, and substitution of detergents for lipids, examining the channel under more native conditions is desirable. Solid-state NMR (SSNMR) can be used to study the wild-type protein under activating conditions (low pH), at room temperature, and in bacteriomimetic liposomes. In this work, we sought to structurally assign the acti- vated state present in SSNMR experiments. We used a combination of molecular dynamics (MD) simulations, chemical shift prediction algorithms, and Bayesian inference techniques to determine which of the most plausible X-ray structures resolved to date best represents the activated state captured in SSNMR. We first identified specific nuclei with simulated NMR chemical shifts that differed significantly when comparing partially open vs. fully open ensembles from MD simulations. The simulated NMR chemical shifts for those spe- cific nuclei were then compared to experimental ones, revealing that the simulation of the partially open state was in good agreement with the SSNMR data. Nuclei that discrimi- nate effectively between partially and fully open states belong to residues spread over the sequence and provide a molecular level description of the conformational change.

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“…Finally the posterior distributions are estimated numerically using the NUTS 58 algorithm. This algorithm also calculates the normalization factor p(d) or the probability of the data.…”

Section: Chemical Shift Prediction From the MD Resultsmentioning

confidence: 99%

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

Pérez-Conesa

Keeler

Zhang

et al. 2020

Preprint

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“…The weather environmental condition and status are predicted using the forecast system based on decision-making and supporting system, and information is stored in the cloud using IoT. [13][14][15][16][17][18][19][20][21][22][23] The IoT is used to fetch all sensor data collected, and accurate weather information is predicted using the proposed methodology of decision-making and supporting system. Rama Krushna Das et al 24 have proposed the smart agriculture farming system using IoT by inspiring the Indian nation's financial contribution basis of profits and employment of around 73%.…”

Section: Related Workmentioning

confidence: 99%

“…The decision‐making and supporting system using cloud technology is needed for improving efficiency and minimizing economic expenditure in the agriculture industry. The weather environmental condition and status are predicted using the forecast system based on decision‐making and supporting system, and information is stored in the cloud using IoT 13‐23 . The IoT is used to fetch all sensor data collected, and accurate weather information is predicted using the proposed methodology of decision‐making and supporting system.…”

Section: Related Workmentioning

confidence: 99%

Precision agriculture and farming using Internet of Things based on wireless sensor network

Sanjeevi

Prasanna

Kumar

et al. 2020

Trans Emerging Tel Tech

Self Cite

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In the recent past, the agriculture and farming industry has become the precision network connectivity of sensors with a new dimension of Internet of Things (IoT) technology. The cloud computing and wireless sensor network-(WSN) based extensive distance network in IoT can be applied to the agriculture and farming industry in a remote area. In this paper, we propose scalable wireless sensor network architecture for monitoring and control using IoT for agriculture and farming in a remote area. One of the significant managements in precision agriculture and farming (PAF) is water resource irrigation and proper utilization of water resources. Appropriate utilization of water irrigation management can be achieved by applying WSN technology using IoT. The efficient communication of various wireless sensors is processed using IoT in PAF to improve the productivity of farmers. We have analyzed the WSN structure based on throughput maximization, latency minimization, high signal-to-noise ratio (SNR), minimum mean square error, and improved coverage area. The experimental results have proved that the proposed methodology provides better performance than conventional IoT-based agriculture and farming.

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“…Two energy-aware scheduling algorithms for independent tasks have been proposed in the work of Sajid et al 24 The algorithms schedule tasks to the processors based on a weighted aggregation cost function, and then, a task migration phase follows. Many other scheduling algorithms for DVFS environments have been proposed in the literature (see other works [25][26][27][28] ). An earlier version of this article has concentrated on an experimental evaluation of T-schedules and E-schedules.…”

Section: Related Workmentioning

confidence: 99%

A scheduling selection process for energy‐efficient task execution on DVFS processors

Rauber

Rünger

2018

Concurrency and Computation

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Summary The efficient execution of parallel programs with respect to execution time and energy consumption is a major concern, and often, scheduling methods are used to achieve a good performance. In this article, we consider the problem of scheduling a set of independent tasks on a parallel system with homogeneous execution units providing frequency scaling. The set of tasks has the property that the tasks exhibit a task‐specific inhomogeneous and non‐linear behavior of their specific time‐energy relation. In addition, it is assumed that execution time and energy consumption behave in a non‐linear manner with respect to frequency scaling. For the assignment of these tasks to execution units, we propose a scheduling selection process combining scheduling algorithms, which determine a task assignment, with a subsequent selection of frequency scaling, which we call schedule execution modes. This process builds a rich set of alternative schedule execution modes from which efficient (or Pareto‐optimal) schedule execution modes can be selected. Experiments are done for the SPEC CPU benchmarks. Experimental results illustrate that the enriched scheduling process leads to task assignments resulting in an efficient execution on DVFS processors.

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NUTS scheduling approach for cloud data centers to optimize energy consumption

Cited by 13 publications

References 31 publications

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

Informing NMR experiments with molecular dynamics simulations to characterize the dominant activated state of the KcsA ion channel

Precision agriculture and farming using Internet of Things based on wireless sensor network

A scheduling selection process for energy‐efficient task execution on DVFS processors

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