The Impact of office productivity cloud computing on energy consumption and greenhouse gas emissions

Cloud computing is usually regarded as being energy efficient and thus emitting less greenhouse gases (GHG) than traditional forms of computing. When the energy consumption of Microsoft’s cloud computing Office 365 (O365) and traditional Office 2010 (O2010) software suites were tested and modeled, some cloud services were found to consume more energy than the traditional form. The developed model in this research took into consideration the energy consumption at the three main stages of data transmission; data center, network, and end user device. Comparable products from each suite were selected and activities were defined for each product to represent a different computing type. Microsoft provided highly confidential data for the data center stage, while the networking and user device stages were measured directly. A new measurement and software apportionment approach was defined and utilized allowing the power consumption of cloud services to be directly measured for the user device stage. Results indicated that cloud computing is more energy efficient for Excel and Outlook which consumed less energy and emitted less GHG than the standalone counterpart. The power consumption of the cloud based Outlook (8%) and Excel (17%) was lower than their traditional counterparts. However, the power consumption of the cloud version of Word was 17% higher than its traditional equivalent. A third mixed access method was also measured for Word which emitted 5% more GHG than the traditional version. It is evident that cloud computing may not provide a unified way forward to reduce energy consumption and GHG. Direct conversion from the standalone package into the cloud provision platform can now consider energy and GHG emissions at the software development and cloud service design stage using the methods described in this research.

Electron acceleration and parallel electric fields due to kinetic Alfvén waves in plasma with similar thermal and Alfvén speeds

We investigate electron acceleration due to shear Alfven waves in a collissionless plasma for plasma parameters typical of 4–5RE radial distance from the Earth along auroral field lines. Recent observational work has motivated this study, which explores the plasma regime where the thermal velocity of the electrons is similar to the Alfven speed of the plasma, encouraging Landau resonance for electrons in the wave fields. We use a self-consistent kinetic simulation model to follow the evolution of the electrons as they interact with a short-duration wave pulse, which allows us to determine the parallel electric field of the shear Alfven wave due to both electron inertia and electron pressure effects. The simulation demonstrates that electrons can be accelerated to keV energies in a modest amplitude sub-second period wave. We compare the parallel electric field obtained from the simulation with those provided by fluid approximations.

Computing Fresnel integrals via modified trapezium rules

In this paper we propose methods for computing Fresnel integrals based on truncated trapezium rule approximations to integrals on the real line, these trapezium rules modified to take into account poles of the integrand near the real axis. Our starting point is a method for computation of the error function of complex argument due to Matta and Reichel (J Math Phys 34:298–307, 1956) and Hunter and Regan (Math Comp 26:539–541, 1972). We construct approximations which we prove are exponentially convergent as a function of N , the number of quadrature points, obtaining explicit error bounds which show that accuracies of 10−15 uniformly on the real line are achieved with N=12 , this confirmed by computations. The approximations we obtain are attractive, additionally, in that they maintain small relative errors for small and large argument, are analytic on the real axis (echoing the analyticity of the Fresnel integrals), and are straightforward to implement.

Median architecture by accumulative parallel counters

The time to process each of W/B processing blocks of a median calculation method on a set of N W-bit integers is improved here by a factor of three compared to the literature. Parallelism uncovered in blocks containing B-bit slices are exploited by independent accumulative parallel counters so that the median is calculated faster than any known previous method for any N, W values. The improvements to the method are discussed in the context of calculating the median for a moving set of N integers for which a pipelined architecture is developed. An extra benefit of smaller area for the architecture is also reported.

Computing journey start times with recurrent traffic conditions

n this study, the authors discuss the effective usage of technology to solve the problem of deciding on journey start times for recurrent traffic conditions. The developed algorithm guides the vehicles to travel on more reliable routes that are not easily prone to congestion or travel delays, ensures that the start time is as late as possible to avoid the traveller waiting too long at their destination and attempts to minimise the travel time. Experiments show that in order to be more certain of reaching their destination on time, a traveller has to leave early and correspondingly arrive early, resulting in a large waiting time. The application developed here asks the user to set this certainty factor as per the task in hand, and computes the best start time and route.

Cloud computing in e-science: research challenges and opportunities

SOA (Service Oriented Architecture), workflow, the Semantic Web, and Grid computing are key enabling information technologies in the development of increasingly sophisticated e-Science infrastructures and application platforms. While the emergence of Cloud computing as a new computing paradigm has provided new directions and opportunities for e-Science infrastructure development, it also presents some challenges. Scientific research is increasingly finding that it is difficult to handle “big data” using traditional data processing techniques. Such challenges demonstrate the need for a comprehensive analysis on using the above mentioned informatics techniques to develop appropriate e-Science infrastructure and platforms in the context of Cloud computing. This survey paper describes recent research advances in applying informatics techniques to facilitate scientific research particularly from the Cloud computing perspective. Our particular contributions include identifying associated research challenges and opportunities, presenting lessons learned, and describing our future vision for applying Cloud computing to e-Science. We believe our research findings can help indicate the future trend of e-Science, and can inform funding and research directions in how to more appropriately employ computing technologies in scientific research. We point out the open research issues hoping to spark new development and innovation in the e-Science field.

What is the right balance for performance and isolation with virtualization in HPC?

The use of virtualization in high-performance computing (HPC) has been suggested as a means to provide tailored services and added functionality that many users expect from full-featured Linux cluster environments. The use of virtual machines in HPC can offer several benefits, but maintaining performance is a crucial factor. In some instances the performance criteria are placed above the isolation properties. This selective relaxation of isolation for performance is an important characteristic when considering resilience for HPC environments that employ virtualization. In this paper we consider some of the factors associated with balancing performance and isolation in configurations that employ virtual machines. In this context, we propose a classification of errors based on the concept of “error zones”, as well as a detailed analysis of the trade-offs between resilience and performance based on the level of isolation provided by virtualization solutions. Finally, a set of experiments are performed using different virtualization solutions to elucidate the discussion.

Ventilation performance in a passage between two non-parallel buildings

A great number of studies on wind conditions in passages between slab-type buildings have been conducted in the past. However, wind conditions under different structure and configuration of buildings is still unclear and studies existed still can’t provide guidance on urban planning and design, due to the complexity of buildings and aerodynamics. The aim of this paper is to provide more insight in the mechanism of wind conditions in passages. In this paper, a simplified passage model with non-parallel buildings is developed on the basis of the wind tunnel experiments conducted by Blocken et al. (2008). Numerical simulation based on CFD is employed for a detailed investigation of the wind environment in passages between two long narrow buildings with different directions and model validation is performed by comparing numerical results with corresponding wind tunnel measurements.

The MELODIES project: integrating diverse data using Linked Data and cloud computing

We present an overview of the MELODIES project, which is developing new data-intensive environmental services based on data from Earth Observation satellites, government databases, national and European agencies and more. We focus here on the capabilities and benefits of the project’s “technical platform”, which applies cloud computing and Linked Data technologies to enable the development of these services, providing flexibility and scalability.

IMF control of cusp proton emission intensity and dayside convection: implications for component and anti-parallel reconnection

We study a brightening of the Lyman-alpha emission in the cusp which occurred in response to a short-lived southward turning of the interplanetary magnetic field (IMF) during a period of strongly enhanced solar wind plasma concentration. The cusp proton emission is detected using the SI-12 channel of the FUV imager on the IMAGE spacecraft. Analysis of the IMF observations recorded by the ACE and Wind spacecraft reveals that the assumption of a constant propagation lag from the upstream spacecraft to the Earth is not adequate for these high time-resolution studies. The variations of the southward IMF component observed by ACE and Wind allow for the calculation of the ACE-to-Earth lag as a function of time. Application of the derived propagation delays reveals that the intensity of the cusp emission varied systematically with the IMF clock angle, the relationship being particularly striking when the intensity is normalised to allow for the variation in the upstream solar wind proton concentration. The latitude of the cusp migrated equatorward while the lagged IMF pointed southward, confirming the lag calculation and indicating ongoing magnetopause reconnection. Dayside convection, as monitored by the SuperDARN network of radars, responded rapidly to the IMF changes but lagged behind the cusp proton emission response: this is shown to be as predicted by the model of flow excitation by Cowley and Lockwood (1992). We use the numerical cusp ion precipitation model of Lockwood and Davis (1996), along with modelled Lyman-_ emission efficiency and the SI-12 instrument response, to investigate the effect of the sheath field clock angle on the acceleration of ions on crossing the dayside magnetopause. This modelling reveals that the emission commences on each reconnected field line 2–2.5min after it is opened and peaks 3–5 min after it is opened. We discuss how comparison of the Lyman-alpha intensities with oxygen emissions observed simultaneously by the SI-13 channel of the FUV instrument offers an opportunity to test whether or not the clock angle dependence is consistent with the “component” or the “anti-parallel” reconnection hypothesis.

Towards a parallel computationally efficient approach to scaling up data stream classification

Advances in hardware technologies allow to capture and process data in real-time and the resulting high throughput data streams require novel data mining approaches. The research area of Data Stream Mining (DSM) is developing data mining algorithms that allow us to analyse these continuous streams of data in real-time. The creation and real-time adaption of classification models from data streams is one of the most challenging DSM tasks. Current classifiers for streaming data address this problem by using incremental learning algorithms. However, even so these algorithms are fast, they are challenged by high velocity data streams, where data instances are incoming at a fast rate. This is problematic if the applications desire that there is no or only a very little delay between changes in the patterns of the stream and absorption of these patterns by the classifier. Problems of scalability to Big Data of traditional data mining algorithms for static (non streaming) datasets have been addressed through the development of parallel classifiers. However, there is very little work on the parallelisation of data stream classification techniques. In this paper we investigate K-Nearest Neighbours (KNN) as the basis for a real-time adaptive and parallel methodology for scalable data stream classification tasks.

Increased dietary α-linolenic acid has sex-specific effects upon eicosapentaenoic acid status in humans: re-examination of data from a randomised, placebo-controlled, parallel study

Background: There is a metabolic pathway by which mammals can convert the omega-3 (n-3) essential fatty acid α-linolenic acid (ALA) into longer-chain n-3 polyunsaturated fatty acids (LC n-3 PUFA) including eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). As far as we know there are currently no studies that have specifically examined sex differences in the LC n-3 PUFA response to increased dietary ALA intake in humans, although acute studies with isotope-labelled ALA identified that women have a significantly greater capacity to synthesise EPA and DHA from ALA compared to men. Findings: Available data from a placebo-controlled, randomised study were re-examined to identify whether there are sex differences in the LC n-3 PUFA response to increased dietary ALA intake in humans. There was a significant difference between sexes in the response to increased dietary ALA, with women having a significantly greater increase in the EPA content of plasma phospholipids (mean +2.0% of total fatty acids) after six months of an ALA-rich diet compared to men (mean +0.7%, P = 0.039). Age and BMI were identified as predictors of response to dietary ALA among women. Conclusions: Women show a greater increase in circulating EPA than men during increased dietary ALA consumption. Further understanding of individual variation in the response to dietary ALA could inform nutrition advice, with recommendations being specifically tailored according to habitual diet, sex, age and BMI.

Precise analysis of array usage in scientific programs

The automatic transformation of sequential programs for efficient execution on parallel computers involves a number of analyses and restructurings of the input. Some of these analyses are based on computing array sections, a compact description of a range of array elements. Array sections describe the set of array elements that are either read or written by program statements. These sections can be compactly represented using shape descriptors such as regular sections, simple sections, or generalized convex regions. However, binary operations such as Union performed on these representations do not satisfy a straightforward closure property, e.g., if the operands to Union are convex, the result may be nonconvex. Approximations are resorted to in order to satisfy this closure property. These approximations introduce imprecision in the analyses and, furthermore, the imprecisions resulting from successive operations have a cumulative effect. Delayed merging is a technique suggested and used in some of the existing analyses to minimize the effects of approximation. However, this technique does not guarantee an exact solution in a general setting. This article presents a generalized technique to precisely compute Union which can overcome these imprecisions.

Major differences of cloud computing adoption in universities: Europe vs. Middle East

The extensive use of cloud computing in educational institutes around the world brings unique challenges for universities. Some of these challenges are due to clear differences between Europe and Middle East universities. These differences stem from the natural variation between people. Cloud computing has created a new concept to deal with software services and hardware infrastructure. Some benefits are immediately gained, for instance, to allow students to share their information easily and to discover new experiences of the education system. However, this introduces more challenges, such as security and configuration of resources in shared environments. Educational institutes cannot escape from these challenges. Yet some differences occur between universities which use cloud computing as an educational tool or a form of social connection. This paper discusses some benefits and limitations of using cloud computing and major differences in using cloud computing at universities in Europe and the Middle East, based on the social perspective, security and economics concepts, and personal responsibility.

Acceleration and visualization of Dynamic Network Optimization

With the emerging prevalence of smart phones and 4G LTE networks, the demand for faster-better-cheaper mobile services anytime and anywhere is ever growing. The Dynamic Network Optimization (DNO) concept emerged as a solution that optimally and continuously tunes the network settings, in response to varying network conditions and subscriber needs. Yet, the DNO realization is still at infancy, largely hindered by the bottleneck of the lengthy optimization runtime. This paper presents the design and prototype of a novel cloud based parallel solution that further enhances the scalability of our prior work on various parallel solutions that accelerate network optimization algorithms. The solution aims to satisfy the high performance required by DNO, preliminarily on a sub-hourly basis. The paper subsequently visualizes a design and a full cycle of a DNO system. A set of potential solutions to large network and real-time DNO are also proposed. Overall, this work creates a breakthrough towards the realization of DNO.