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

Abstract

www.amtec-medical.com Biotechnologies such as genomics, gene sequencing and highthroughput screening are creating massive volumes and multiple sources of biological and chemical data. However, the volumes of data and the processing power required to analyse it, is threatening to create a bottleneck that might hamper the growth of biotechnology itself. To date, the HPC resources required to store, manage and analyse such volumes of data has been only at the disposal of large companies and research institutes. However, with the emergence of Grid Technology, the whole area of bioinformatics is an ideal candidate to leverage the benefits of secure, reliable and scaleable high bandwidth access to distributed data sources across various administrative domains. This in effect will allow geographically remote researchers with limited internal resources, access to a wealth of biological datasets and HPC resources. This paper presents from an industrial perspective the business drivers that acted as the catalyst in creating the industrial e-Science project GeneGrid. The Architecture and roadmap for a Grid based Virtual Bioinformatics Laboratory will be presented.

Optimising Physiochemical Japanese Knotweed Control

<p>Presentation delivered at the Amenity Forum Conference on 13/10/16 in Burton-on-Trent (UK).</p

Disentangling Japanese Knotweed

<p>Poster presentation delivered at the BCPC Annual Weed Review 2016 on the 10/11/16 at Rothamstead Research (UK).</p