Transient Cloud Research Articles

Enabling the execution of HPC applications on public clouds with HPC@Cloud toolkit

AbstractThe advent of cloud computing has made access to computing infrastructure available to millions of users that face resource constraints. In the context of high performance computing (HPC), public cloud resources have emerged as a cost‐effective alternative to expensive on‐premises clusters. However, there are several challenges and limitations in adopting this approach. This paper proposes HPC@Cloud , a provider‐agnostic open‐source software toolkit that facilitates the migration, testing, and execution of HPC applications in public clouds. The toolkit takes advantage of various fault tolerance technologies to enable the use of inexpensive transient cloud infrastructure, commonly known as “spot” instances. Also, it features integration with singularity containers, allowing users to run complex applications on virtual HPC clusters in a portable and reproducible way. Finally, it provides a data‐based empirical approach to estimating cloud infrastructure costs for HPC workloads. The results obtained on two public cloud providers (AWS and Vultr) show that: (i) HPC@Cloud can efficiently build virtual HPC clusters on the cloud; (ii) the new adaptive fault tolerance strategy outperforms other existing strategies based on blocking restoration; (iii) the integration of singularity containers into HPC@Cloud improves the portability of HPC applications to public clouds with negligible performance penalty to the applications; (iv) the proposed cost prediction approach can estimate the cost of running the applications on AWS and Vultr with up to 93% accuracy on average.

The emergence of a new wintertime Arctic energy balance regime

The modern Arctic climate during wintertime is characterized by sea-ice cover, a strong surface temperature inversion, and the absence of convection. Correspondingly, the energy balance in the Arctic atmosphere today is dominated by atmospheric radiative cooling and advective heating, so-called radiative advective equilibrium. Climate change in the Arctic involves sea-ice melt, vanishing of the surface inversion, and emergence of convective precipitation. Here we show climate change in the Arctic involves the emergence of a new energy balance regime characterized by radiative cooling, convective heating, and advective heating, so-called radiative convective advective equilibrium. A time-dependent decomposition of the atmospheric energy balance shows the regime transition is associated with enhanced radiative cooling followed by decreased advective heating. The radiative cooling response consists of a robust clear-sky greenhouse effect and a transient cloud contribution that varies across models. Mechanism-denial experiments in an aquaplanet with and without interactive sea ice highlight the important role of sea-ice melt in both the radiative cooling and advective heating responses. The results show that climate change in the Arctic involves temporally evolving mechanisms, suggesting that an emergent constraint based on historical data or trends may not constrain the long-term response.

Global Radiative Flux Profile Data Set: Revised and Extended

AbstractThe third generation of the radiative flux profile data product, called ISCCP‐FH, is described. The revisions over the previous generation (called ISCCP‐FD) include improvements in the radiative model representation of gaseous and aerosol effects, as well as a refined statistical model of cloud vertical layer variations with cloud types, and increased spatial resolution. The new product benefits from the changes in the new H‐version of the ISCCP cloud products (called ISCCP‐H): higher spatial resolution, revised radiance calibration and treatment of ice clouds, treatment of aerosol effects, and revision of all the ancillary atmosphere and surface property products. The ISCCP‐FH product is evaluated against more direct measurements from the Clouds and the Earth’s Radiant Energy System and the Baseline Surface Radiation Network products, showing some small, overall reductions in average flux uncertainties; but the main results are similar to ISCCP‐FD: the ISCCP‐FH uncertainties remain ≲10 Wm−2 at the top‐of‐atmosphere (TOA) and ≲15 Wm−2 at surface for monthly, regional averages. The long‐term variations of TOA, surface and in‐atmosphere net fluxes are documented and the possible transient cloud feedback implications of a long‐term change of clouds are investigated. The cloud and flux variations from 1998 to 2012 suggest a positive cloud‐radiative feedback on the oceanic circulation and a negative feedback on the atmospheric circulation. This example demonstrates that the ISCCP‐FH product can provide useful diagnostic information about weather‐to‐interannual scale variations of radiation induced by changes in cloudiness as well as atmospheric and surface properties.

Consequences of dynamically unstable moons in extrasolar systems

ABSTRACT Moons orbiting rocky exoplanets in compact orbits about other stars experience an accelerated tidal evolution, and can either merge with their parent planet or reach the limit of dynamical instability within a Hubble time. We review the parameter space over which moons become unbound, including the effects of atmospheric tides on the planetary spin. We find that such tides can change the final outcome from merger to escape, albeit over a limited parameter space. We also follow the further evolution of unbound moons, and demonstrate that the overwhelmingly most likely long-term outcome is that the unbound moon returns to collide with its original parent planet. The dust released by such a collision is estimated to reach optical depths $\sim 10^{-3}$, exhibit characteristic temperatures of a few hundred degrees kelvin, and last for a few thousand years. These properties make such events an attractive model for the emerging class of middle-aged main-sequence stars that are observed to show transient clouds of warm dust. Furthermore, a late collision between a planet and a returning moon on a hyperbolic orbit may sterilize an otherwise habitable planet.

Regulation strategies for mitigating voltage fluctuations induced by photovoltaic solar systems in an urban low voltage grid

Transient clouds cause rapid changes in the power output of Photovoltaic (PV) solar systems. These ramp rates may lead to power quality problems, such as voltage fluctuations, in the low-voltage (LV) electricity grid. This paper firstly assesses the impact of a growing number of distributed PV systems on the voltage profile in a LV grid by considering PV penetration rates of 40%, 70% and 100% of the local rooftop capacity. Next, the potential of active power curtailment, grid reinforcement and supercapacitors to prevent or mitigate these voltage fluctuations are examined. The experiments in this study are based on simulations run with a two-second time resolution for an urban LV grid located in Utrecht, the Netherlands. This study identifies that problematic fluctuations occur already at a 40% PV penetration rate and are expected up to 7.4% of time for a 100% PV penetration scenario. Additionally, the local deployment of either active power curtailment or supercapacitors are identified as adequate strategies to regulate the occurring voltage fluctuations. Finally, the most stable voltage profile and the lowest number of problematic voltage fluctuations are found in case of adopting supercapacitors as part of the PV system.

Effects of the meteorological data resolution and aggregation on the optimal design of photovoltaic power plants

The accuracy of the simulation and optimization of ground-mounted photovoltaic plants depends on the reliability of the meteorological datasets, which is affected by their source, length, and resolution. Quantifying the effect of the irradiance data temporal resolution on the optimal design parameters and the expected profitability is important to improve the credibility of photovoltaic design simulations. The optimal values of nine important design parameters, the annual energy yield, and the levelized cost of electricity are calculated for 50 Baseline Surface Radiation Network stations by an automatic photovoltaic optimization method based on datasets with six different resolutions created by two aggregation methods. The aggregation by averaging suppresses the high irradiance values resulting from the transient cloud enhancement effect, while the aggregation by sampling a single value from the middle of each aggregation interval can retain the original distribution of minute-resolution data. The optimization based on averaged hourly data underestimates the levelized cost of electricity by up to 3%, overestimates the inverter sizing ratio by 0.05 on average, and the tilt angle by up to 5° compared to the high-resolution datasets. The datasets aggregated by sampling provide more reliable results even at lower resolutions; therefore, it can be an effective technique for accurate photovoltaic optimization without the long calculation time of the minute-resolution simulation.

Characterizing Subsiding Shells in Shallow Cumulus Using Doppler Lidar and Large‐Eddy Simulation

AbstractThe existence of subsiding shells on the periphery of shallow cumulus clouds has major implications concerning the parameterization of shallow convection, with the mass exchange between the shell and cloudy air representing a significant deviation from the commonly used bulk‐plume parameterization. We examine the structure and frequency of subsiding shells in shallow cumulus convection using Doppler lidars at the Atmospheric Radiation Measurement Southern Great Plains facility in the central United States and at the Jülich ObservatorY for Cloud Evolution in western Germany. Doppler lidar indicates that the vertical subsiding shell extent is asymmetric, while shell width is typically ~100 m. Large‐eddy simulation can reasonably simulate the observed shell structure using a grid spacing of 10 m and suggests that much of the observed asymmetry is not a result of transient cloud evolution.

A 100 kW cavity-receiver reactor with an integrated two-step thermochemical cycle: Thermal performance under solar transients

A future sustainable economy based on hydrogen will require large-scale hydrogen production processes in a CO2 emission-free way. Within this context, solar-driven thermochemical water splitting cycles have been proposed as a promising alternative for hydrogen mass production with the use of concentrated solar energy as the principal source to provide the process heat.Numerous solar thermochemical water-splitting cycles have been investigated for hydrogen production, each with different sets of operating conditions, engineering challenges, etc. Challenges remain in the demonstration of commercially viable thermochemical cycles and reactors, in particular, efficient and robust reactor designs compatible with solar concentrating systems. A 100 kWth multi-tubular cavity reactor for hydrogen production integrated in a solar tower has been used as test bed to demonstrate the technological feasibility of a thermochemical process with incident solar transients.The work presented on this paper dealt with integration of a cavity reactor into a solar concentrating system running a ferrite based solar thermochemical water splitting cycle. This work also explores the thermal performance of a cavity reactor beyond optimal operational conditions governed by transient cloud events. These conditions emerge as a relevant matter to be considered because they have not been studied so far.

Analytical and computational indoor shelter models for infiltration of carbon dioxide into buildings: Comparison with experimental data

This paper describes two indoor shelter models – an analytical model and a Computational Fluid Dynamics (CFD) model - that can be used to predict the level of infiltration of carbon dioxide (CO2) into a building following a release from an onshore CO2 pipeline. The motivation behind the development of these models was to demonstrate that the effects of shelter should be considered as part of a Quantitative Risk Assessment (QRA) for CO2 pipeline infrastructure and to provide a methodology for considering the impact of a CO2 release on building occupants.A key component in the consequence modelling of a release from a CO2 pipeline is an infiltration model for CO2 into buildings which can describe the impact on people inside buildings during a release event.This paper describes the development of an analytical shelter model and a CFD model which are capable of predicting the change in internal concentration, temperature and toxic load within a single roomed building that is totally engulfed by a transient cloud of gaseous CO2. Application of the models is demonstrated by comparison with experimental measurements of CO2 accumulation in a building placed in the path of a drifting cloud of CO2. The analytical and CFD models are shown to make good predictions of the average change in internal concentration. Furthermore, it is demonstrated that the effects of shelter should be taken into account when conducting QRA assessments on CO2 pipelines.

A high‐performance IoT solution to reduce frost damages in stone fruits

SummaryAgriculture is one of the key sectors where technology is opening new opportunities to break up the market. The Internet of Things (IoT) could reduce the production costs and increase the product quality by providing intelligence services via IoT analytics. However, the hard weather conditions and the lack of connectivity in this field limit the successful deployment of such services as they require both, ie, fully connected infrastructures and highly computational resources. Edge computing has emerged as a solution to bring computing power in close proximity to the sensors, providing energy savings, highly responsive web services, and the ability to mask transient cloud outages. In this paper, we propose an IoT monitoring system to activate anti‐frost techniques to avoid crop loss, by defining two intelligent services to detect outliers caused by the sensor errors. The former is a nearest neighbor technique and the latter is the k‐means algorithm, which provides better quality results but it increases the computational cost. Cloud versus edge computing approaches are analyzed by targeting two different low‐power GPUs. Our experimental results show that cloud‐based approaches provides highest performance in general but edge computing is a compelling alternative to mask transient cloud outages and provide highly responsive data analytic services in technologically hostile environments.

Cloud height and tracking accuracy of three all sky imager systems for individual clouds

Solar irradiance nowcasts can be derived with sky images from all sky imagers (ASI) by detecting and analyzing transient clouds, which are the main contributor of intra-hour solar irradiance variability. The accuracy of ASI based solar irradiance nowcasting systems depends on various processing steps. Two vital steps are the cloud height detection and cloud tracking. This task is challenging, due to the atmospheric conditions that are often complex, including various cloud layers moving in different directions simultaneously.This challenge is addressed by detecting and tracking individual clouds. For this, we developed two distinct ASI nowcasting approaches with four or two cameras and a third hybridized approach. These three systems create individual 3-D cloud models with unique attributes including height, position, size, optical properties and motion. This enables us to describe complex multi-layer conditions.In this paper, derived cloud height and motion vectors are compared with a reference ceilometer (height) and shadow camera system (motion) over a 30 day validation period. The validation data set includes a wide range of cloud heights, cloud motion patterns and atmospheric conditions. Furthermore, limitations of ASI based nowcasting systems due to image resolution and image perspective constrains are discussed.The most promising system is found to be the hybridized approach. This approach uses four ASIs and a voxel carving based cloud modeling combined with a cloud segmentation independent stereoscopic cloud height and tracking detection. We observed for this approach an overall mean absolute error of 648 m for the height, 1.3 m/s for the cloud speed and 16.2° for the motion direction.

Do we detect interplanetary dust with Faraday cups?

Transient clouds of a plasma generated by hypervelocity dust particles impacting onto the spacecraft were observed in-situ by many experiments over the last 20 years. The reported observations analyze sensitive measurements of plasma waves that are transmitted to the Earth with a sufficient time resolution. The detection is based on a fact that hypervelocity impacts generate plumes of the ionized gas expanding into a space. The present paper analyzes five years of the operation of the Bright Monitor of the Solar Wind (BMSW) onboard the Spektr-R spacecraft with a motivation to demonstrate that such type of the instruments is capable to observe the dust impacts into its detectors. The results of analysis are compared with Wind electric field measurements used for a detection of hypervelocity dust impacts.

Spatiotemporal interpolation and forecast of irradiance data using Kriging

Solar power variability is a concern to grid operators as unanticipated changes in PV plant power output can strain the electric grid. The main cause of solar variability is clouds passing over PV modules. However, geographic diversity across a region leads to a reduction in the cloud-induced variability. In this paper, spatiotemporal correlations of irradiance data are analyzed and spatial and spatiotemporal ordinary Kriging methods are applied to model irradiation at an arbitrary point based on the given time series of irradiation at some observed locations. The correlations among the irradiances at observed locations are modeled by general parametric covariance functions. Besides the isotropic covariance function (which is independent of direction), a new non-separable anisotropic parametric covariance function is proposed to model the transient clouds. Also, a new approach is proposed to estimate the spatial and temporal decorrelation distances analytically using the applied parametric covariance functions, which reduce the size of the computations without loss in accuracy (parameter shrinkage). The analysis has been performed and the Kriging method is first validated by using two spatially and temporally resolved artificial irradiance datasets generated from Large Eddy Simulation. Then, the spatiotemporal Kriging method is applied on real irradiance and output power data in California (Sacramento and San Diego areas) where the cloud motion had to be estimated during the process using cross-correlation method (CCM). Results confirm that the anisotropic model is most accurate with an average normalized root mean squared error (nRMSE) of 7.92% representing a 66% relative improvement over the persistence model.

Assignment and collaborative execution of tasks on transient clouds

Transient clouds (TC) are temporal clouds that enable nearby mobile devices to form an ad hoc network and advertise their capabilities as cloud services. Through utilizing the collective power of the group, devices are no longer constrained by their local hardware and software capabilities. TC harness the ubiquitous nature of mobile devices along with their ever-increasing sets of capabilities in providing a rich computing platform. In this paper, we present two instantiations of task assignment algorithms that achieve various goals such as balancing the load on devices and minimizing the cost of communication. In the first instantiation, we consider a centralized approach in which a cluster head is responsible for maintaining the list of capabilities and assigning tasks to devices based on their capabilities. We present a modified version of the Hungarian method that allows for balancing the load on devices. In the second instantiation, we consider a distributed approach in which devices advertise and find capabilities through an overlay network. The overlay is designed to capitalize on locality and thus seeks to minimize the cost in finding devices with certain capabilities. We evaluate the performance of our TC through extensive simulation experiments complemented by a realistic implementation on a set of devices.

The Emergence of Edge Computing

Industry investment and research interest in edge computing, in which computing and storage nodes are placed at the Internet's edge in close proximity to mobile devices or sensors, have grown dramatically in recent years. This emerging technology promises to deliver highly responsive cloud services for mobile computing, scalability and privacy-policy enforcement for the Internet of Things, and the ability to mask transient cloud outages. The web extra at www.youtube.com/playlist?list=PLmrZVvFtthdP3fwHPy_4d61oDvQY_RBgS includes a five-video playlist demonstrating proof-of-concept implementations for three tasks: assembling 2D Lego models, freehand sketching, and playing Ping-Pong.

AN EFFICIENT DISTRIBUTED KEY GENERATION PROTOCOL FOR TRANSIENT CLOUDS

Cloud computing presents a new approach to allow the development of dynamic, distributed and highly scalable software (e.g., networks, servers, storage, applications, and services) that can be rapidly supplied and allowed us with minimal management effort or service provider interaction. Cloud computing provides many advantages to its customers but failing to solve information security concerns. Strong encryption with key management is one of the core mechanisms that Cloud Computing systems should use to secure data, so key management is an important technology that can help secure applications and data in the cloud. In this paper, a proposed elliptic curve based distributed key generation (ECDKG) scheme for Transient Clouds is presented. Performance analysis showed that this scheme not only has strong security, but also has less computational and communication costs.

GMC evolution in a barred spiral galaxy with star formation and thermal feedback

We explore the impact of star formation and thermal stellar feedback on the giant molecular cloud (GMC) population forming in a M83-type barred spiral galaxy. We compare three high-resolution simulations (1.5 pc cell size) with different star formation/feedback models: one with no star formation, one with star formation but no feedback, and one with star formation and thermal energy injection. We analyze the resulting population of clouds, finding that we can identify the same population of massive, virialized clouds and transient, low-surface density clouds found in our previous work (that did not include star formation or feedback). Star formation and feedback can affect the mix of clouds we identify. In particular, star formation alone simply converts dense cloud gas into stars with only a small change to the cloud populations, principally resulting in a slight decrease in the transient population. Feedback, however, has a stronger impact: while it is not generally sufficient to entirely destroy the clouds, it does eject gas out of them, increasing the gas density in the inter-cloud region. This decreases the number of massive clouds, but substantially increases the transient cloud population. We also find that feedback tends to drive a net radial inflow of massive clouds, leading to an increase in the star formation rate in the bar region. We examine a number of possible reasons for this and conclude that it is possible that the drag force from the enhanced intercloud density could be responsible.

Investigation of Uttarakhand (India) disaster-2013 using weather research and forecasting model

A natural disaster in the form of severe flash floods due to extreme precipitation occurred at Kedarnath (Uttarakhand), India, on 16–17 June 2013 and is being considered as one of the worst disasters in India (Das in J Geol Soc India 82:201, 2013). The catastrophe in the form of flash flood and associated debris flow caused major devastation leading to a high death toll of locals and visiting pilgrims. The very early migration of monsoon trough (MT) towards northern India and its interaction with an incoming western disturbance (WD) formed a transient cloud system that led to extreme precipitation. Using WRF model with triple-nested domain for simulation at finer resolutions, this high-intensity precipitating event is analysed. Interaction of the MT with WD over the foothills of the Himalayas usually causes a break period in the Indian monsoon, but the interaction of MT and WD during this storm event showed different characteristics. Such an association of WD with the MT has been termed as pulsatory extension of the monsoon (PEM) towards Himalayas (Pisharoty and Desai in Indian J Meteorol Geophys 7:333–338, 1956; Mooley in Indian J Meteorol Hydrol Geophys 8:253–260, 1957). The interaction of the WD with the MT exactly over the Uttarakhand region forms an occluded discontinuity between the mid to upper-tropospheric WD frontal system (colder) and the lower-troposphere MT (warm and humid). The precursor of this front caused formation of steep temperature gradient over the Indian region that led to the early advance of MT towards Himalayas. Formation of this strong front develops augmented convective instability, which is further enhanced by orographic lifting, leading to the configuration of this large organized storm causing extreme precipitation over a large spatial region.

Context‐awareness over transient cloud in D2D networks: energy performance analysis and evaluation

AbstractThe exponential increase in the number and types of mobile devices, along with their ever‐growing sets of capabilities, have enabled the development of new architectures that aim to harness such heterogeneity. Transient clouds are examples of mobile clouds, which are created on‐the‐fly by the devices present in an environment to share their physical resources (e.g. CPU, memory and network) and would disappear as the nodes leave the network. They enable a device to go beyond its own physical limitations through utilising the capabilities offered by nearby devices over an ad hoc network. This idea exploits the device‐to‐device (D2D) communications paradigm, which allows two nearby devices to communicate with each other in the licenced cellular bandwidth without a base station involved.In this paper, we present a transient context‐aware cloud (TCAC) paradigm based on the assumption that the nodes of the network care more about providing/learning higher level functionalities rather than lower level capabilities in D2D scenario. The proposed architecture, realised by using a WiFi Direct, can be portable through any paradigm, which exploits the D2D communications, so opening the doors to forthcoming 5G scenarios.We present a prototype implementation of our architecture over Android smartphones connected via WiFi Direct along with the performance metrics (power/energy consumption and accuracy) to show the benefits of TCAC. A theoretical and analytical model for the energy consumption related to a device within the TCAC is provided as well. Copyright © 2015 John Wiley & Sons, Ltd.

A CFD based explosion risk analysis methodology using time varying release rates in dispersion simulations

A full probabilistic Explosion Risk Analysis (ERA) is commonly used to establish overpressure exceedance curves for offshore facilities. This involves modelling a large number of gas dispersion and explosion scenarios. Capturing the time dependant build up and decay of a flammable gas cloud size along with its shape and location are important parameters that can govern the results of an ERA. Dispersion simulations using Computational Fluid Dynamics (CFD) are generally carried out in detailed ERA studies to obtain these pieces of information. However, these dispersion simulations are typically modelled with constant release rates leading to steady state results. The basic assumption used here is that the flammable gas cloud build up rate from these constant release rate dispersion simulations would mimic the actual transient cloud build up rate from a time varying release rate. This assumption does not correctly capture the physical phenomena of transient gas releases and their subsequent dispersion and may lead to very conservative results. This in turn results in potential over design of facilities with implications on time, materials and cost of a project.In the current work, an ERA methodology is proposed that uses time varying release rates as an input in the CFD dispersion simulations to obtain the fully transient flammable gas cloud build-up and decay, while ensuring the total time required to perform the ERA study is also reduced. It was found that the proposed ERA methodology leads to improved accuracy in dispersion results, steeper overpressure exceedance curves and a significant reduction in the Design Accidental Load (DAL) values whilst still maintaining some conservatism and also reducing the total time required to perform an ERA study.