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

Abstract Abstract 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) can offer significant savings. In this paper, a software abstraction layer is used to discover the most appropriate infrastructure resources for a given application, by applying a two-phase constraints-based approach to a multi-provider cloud environment. In the first phase, a set of possible infrastructure resources is identified for the application. In the second phase, a suitable heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic may be most appropriate; for others a performance-based heuristic may be of greater relevance. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental results show that the proposed model can dynamically select appropriate resouces for an application’s requirements. </jats:sec

Carotenoid Distribution in Living Cells of Haematococcus pluvialis (Chlorophyceae)

Haematococcus pluvialis is a freshwater unicellular green microalga belonging to the class Chlorophyceae and is of commercial interest for its ability to accumulate massive amounts of the red ketocarotenoid astaxanthin (3,3′-dihydroxy-β,β-carotene-4,4′-dione). Using confocal Raman microscopy and multivariate analysis, we demonstrate the ability to spectrally resolve resonance–enhanced Raman signatures associated with astaxanthin and β-carotene along with chlorophyll fluorescence. By mathematically isolating these spectral signatures, in turn, it is possible to locate these species independent of each other in living cells of H. pluvialis in various stages of the life cycle. Chlorophyll emission was found only in the chloroplast whereas astaxanthin was identified within globular and punctate regions of the cytoplasmic space. Moreover, we found evidence for β-carotene to be co-located with both the chloroplast and astaxanthin in the cytosol. These observations imply that β-carotene is a precursor for astaxanthin and the synthesis of astaxanthin occurs outside the chloroplast. Our work demonstrates the broad utility of confocal Raman microscopy to resolve spectral signatures of highly similar chromophores in living cells

The selective recruitment of mRNA to the ER and an increase in initiation are important for glucose-stimulated proinsulin synthesis in pancreatic β-cells

Glucose acutely stimulates proinsulin synthesis in pancreatic β-cells through a poorly understood post-transcriptional mechanism. In the present study, we demonstrate in pancreatic β-cells that glucose stimulates the recruitment of ribosome-associated proinsulin mRNA, located in the cytoplasm, to the ER (endoplasmic reticulum), the site of proinsulin synthesis, and that this plays an important role in glucose-stimulated proinsulin synthesis. Interestingly, glucose has greater stimulatory effect on the recruitment of proinsulin mRNA to the ER compared with other mRNAs encoding secretory proteins. This, as far as we are aware, is the first example whereby mRNAs encoding secretory proteins are selectively recruited to the ER and provides a novel regulatory mechanism for secretory protein synthesis. Contrary to previous reports, and importantly in understanding the mechanism by which glucose stimulates proinsulin synthesis, we demonstrate that there is no large pool of ‘free’ proinsulin mRNA in the cytoplasm and that glucose does not increase the rate of de novo initiation on the proinsulin mRNA. However, we show that glucose does stimulate the rate of ribosome recruitment on to ribosome-associated proinsulin mRNA. In conclusion, our results provide evidence that the selective recruitment of proinsulin mRNA to the ER, together with increases in the rate of initiation are important mediators of glucose-stimulated proinsulin synthesis in pancreatic β-cells