-Cloud computing offers the potential to dramatically reduce the cost of software services through the commoditization of information technology assets and ondemand usage patterns. However, the complexity of determining resource provision policies for applications in such complex environments introduces significant inefficiencies and has driven the emergence of a new class of infrastructure called Platform-as-a-Service (PaaS). In this paper, we present a novel PaaS architecture being developed in the EU IST IRMOS project targeting real-time Quality of Service (QoS) guarantees for online interactive multimedia applications. The architecture considers the full service lifecycle including service engineering, service level agreement design, provisioning and monitoring. QoS parameters at both application and infrastructure levels are given specific attention as the basis for provisioning policies in the context of temporal constraints. The generic applicability of the architecture is being verified and validated through implemented scenarios from three important application sectors (film post-production, virtual augmented reality for engineering design, collaborative e-Learning in virtual worlds).
It has recently been shown that digital filtering methods may be used to selectively enhance or suppress the vibrational motion in a molecular dynamics computer simulation solely on the basis of frequency (J. Chem. Phys. 2000, 112, 2586−2597). The method of digitally filtered molecular dynamics (DFMD) does, however, suffer from a number of disadvantages, the most important of which is the rapid redistribution of energy from the selected frequency range in condensed phase simulations. Here, an extension of the DFMD method that solves this problem, reversible digitally filtered molecular dynamics (RDFMD), is presented. In RDFMD, the digital filter is applied successively to velocities that have been generated from previous applications of the filter, by the simple expedient of running simulations both forward and backward in time to fill the filter buffer after each filter application. In this way, kinetic energy is added slowly to the system, with the result that the conformational transitions observed are more controlled and realistic. The method is applied to a number of systems of increasing complexity including alanine dipeptide in gas and condensed phases. These studies demonstrate the advantage of adding energy gradually and also reveal a change in the characteristic frequency of critical vibrations as the transition state is approached. A protocol for applying RDFMD to protein systems has also been devised and tested on the YPGDV pentapeptide in water.
Abstract-With increasing availability of Cloud computing services, this paper addresses the challenge consumers of Infrastructure-as-a-Service (IaaS) have in determining which IaaS provider and resources are best suited to run an application that may have specific Quality of Service (QoS) requirements. Utilising application modelling to predict performance is an attractive concept, but is very difficult with the limited information IaaS providers typically provide about the computing resources. This paper reports on an initial investigation into using Dwarf benchmarks to measure the performance of virtualised hardware, conducting experiments on BonFIRE and Amazon EC2. The results we obtain demonstrate that labels such as 'small', 'medium', 'large' or a number of ECUs are not sufficiently informative to predict application performance, as one might expect. Furthermore, knowing the CPU speed, cache size or RAM size is not necessarily sufficient either as other complex factors can lead to significant performance differences. We show that different hardware is better suited for different types of computations and, thus, the relative performance of applications varies across hardware. This is reflected well by Dwarf benchmarks and we show how different applications correlate more strongly with different Dwarfs, leading to the possibility of using Dwarf benchmark scores as parameters in application models.
A new method for modifying the course of a molecular dynamics computer simulation is presented. Digitally filtered molecular dynamics (DFMD) applies the well-established theory of digital filters to molecular dynamics simulations, enabling atomic motion to be enhanced or suppressed in a selective manner solely on the basis of frequency. The basic theory of digital filters and its application to molecular dynamics simulations is presented, together with the application of DFMD to the simple systems of single molecules of water and butane. The extension of the basic theory to the condensed phase is then described followed by its application to liquid phase butane and the Syrian hamster prion protein. The high degree of selectivity and control offered by DFMD, and its ability to enhance the rate of conformational change in butane and in the prion protein, is demonstrated.
The Hilbert−Huang transform (HHT) is a new method for the analysis of nonstationary signals that allows a signal's frequency and amplitude to be evaluated with excellent time resolution. In this paper, the HHT method is described, and its performance is compared with the Fourier methods of spectral analysis. The HHT is then applied to the analysis of molecular dynamics simulation trajectories, including enhanced sampling trajectories produced by reversible digitally filtered molecular dynamics. Amplitude-time, amplitude-frequency, and amplitude-frequency-time spectra are all produced with the method and compared to equivalent results obtained using wavelet analysis. The wavelet and HHT analysis yield qualitatively similar results, but the HHT provides a better match to physical intuition than the wavelet transform. Moreover the HHT method is able to show the flow of energy into low-frequency vibrations during conformational change events and is able to identify frequencies appropriate for amplification by digital filters including the observation of a 10 cm-1 shift in target frequency.
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