A constraints-based resource discovery model for multi-provider cloud environments

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

Rapid Implementation and Optimisation of DSP Systems on SoPC Heterogeneous Platforms

The emergence of programmable logic devices as processing platforms for digital signal processing applications poses challenges concerning rapid implementation and high level optimization of algorithms on these platforms. This paper describes Abhainn, a rapid implementation methodology and toolsuite for translating an algorithmic expression of the system to a working implementation on a heterogeneous multiprocessor/field programmable gate array platform, or a standalone system on programmable chip solution. Two particular focuses for Abhainn are the automated but configurable realisation of inter-processor communuication fabrics, and the establishment of novel dedicated hardware component design methodologies allowing algorithm level transformation for system optimization. This paper outlines the approaches employed in both these particular instances.

Core-based Methodology: An Automated Approach for Implementing a Complete System From Algorithms to a Heterogeneous Network Including FPGAs

In this paper, we present a methodology for implementing a complete Digital Signal Processing (DSP) system onto a heterogeneous network including Field Programmable Gate Arrays (FPGAs) automatically. The methodology aims to allow design refinement and real time verification at the system level. The DSP application is constructed in the form of a Data Flow Graph (DFG) which provides an entry point to the methodology. The netlist for parts that are mapped onto the FPGA(s) together with the corresponding software and hardware Application Protocol Interface (API) are also generated. Using a set of case studies, we demonstrate that the design and development time can be significantly reduced using the methodology developed.

Low temperature conditions in building sandstone: the role of extreme events in temperate environments

Data on rock temperatures has previously been collected to characterise typical diurnal regimes, and more recently to describe short-term variability in extreme locations. However, there is also the case that little is understood concerning the impact of extreme events in otherwise temperate environments. Internal stone temperatures (5?cm) collected during the atypical cold extreme experienced, throughout the UK, in December 2010 show a difference between ambient air temperatures and aspect-related thermal differences, particularly concerning temperature lows and the influence of radiative heating. In this case, debris release was not visible; however, laboratory simulations have shown that under such conditions, surface loss does not necessarily negate the occurrence of internal stone modifications. This preparatory sequence of change demonstrates that surface loss is not the result of one process, but rather many operating over time to sufficiently decrease stone strength to facilitate obvious damage.

The Klondike goldfields and Pleistocene environments of Beringia

The Klondike goldfields of Yukon, Canada, contain a key record of Pleistocene Beringia, the region of Alaska, Siberia, and Yukon that remained largely unglaciated during the late Cenozoic. A concentration of mining exposures, with relict permafrost that is locally more than 700,000 years old, provides exceptional preservation of paleoenvironmental archives and a new perspective on the nature of paleoenvironments during the Pleistocene. A critical feature is the stratigraphic association of distal tephra beds with these paleoenvironmental archives, which facilitates their regional correlation and, in many cases, provides independent ages for the paleoenvironmental assemblages. Paleoenvironmental analyses of fossil arctic ground-squirrel middens and buried vegetation indicate the presence of cryoxerophilous ("steppe-tundra") vegetation growing on well-drained substrates with deep active layers (seasonal thaw depths) during cold intervals of the Pleistocene. Studies of full-glacial paleosols and cryostratigraphic relations of associated ground ice indicate the importance of active loess deposition and surface vegetation cover in maintaining the functionally distinct mammoth-steppe biome, which supported grazing mega-fauna populations, including mammoth, horse, and bison.

IO Performance Prediction in Consolidated Virtualized Environments

We propose a trace-driven approach to predict the performance degradation of disk request response times due to storage device contention in consolidated virtualized environments. Our performance model evaluates a queueing network with fair share scheduling using trace-driven simulation. The model parameters can be deduced from measurements obtained inside Virtual Machines (VMs) from a system where a single VM accesses a remote storage server. The parameterized model can then be used to predict the effect of storage contention when multiple VMs are consolidated on the same virtualized server. The model parameter estimation relies on a search technique that tries to estimate the splitting and merging of blocks at the the Virtual Machine Monitor (VMM) level in the case of multiple competing VMs. Simulation experiments based on traces of the Postmark and FFSB disk benchmarks show that our model is able to accurately predict the impact of workload consolidation on VM disk IO response times.