Models in the Cloud: Generative Software Frameworks to Support the Execution of Environmental Models in the Cloud

云计算是过去几年最重要的技术发展之一，该技术对社会和经济的许多领域产生了重大和变革性的影响。例如，云计算支持智能城市、电子商务和电子政务的发展，并提供支撑数据科学的存储和计算能力(参见。大数据)。然而，云计算提供的软件支持还处于初级阶段，并且是针对特定类型的应用程序量身定做的。对于云中的计算来说尤其如此，在云中，计算框架MapReduce提供的编程方法占主导地位，但MapReduce采用了一种特定的编程风格，其中潜在的海量数据集在通过关联的Reduct()操作整理结果之前通过map()操作进行分析。这是非常强大但非常有限的。同时，研究人员也有兴趣在许多其他应用领域实现云计算的好处。该项目侧重于云计算对环境科学的支持，特别是对云中可能复杂的环境模型的执行。这是一个具有重大意义的领域，环境模拟是评估围绕洪水/干旱、粮食安全和气候变化影响(对经济和社会产生重大后果)的不确定性、风险评估和缓解战略的关键工具。我们特别关注平台即服务(PaaS)关键领域的原理和技术，它是云计算的有效中间件。主要的见解是，PaaS级别的服务需要更仔细地针对关键应用程序域的需求进行定制，包括但不限于支持执行复杂的环境模型。我们提倡一种基于模型驱动工程和软件框架相结合的新方法，并认为这使得云计算为特定应用领域提供的灵活和量身定制的支持方面实现了范式转变。这项工作的主要受益者包括从事模型驱动工程和云计算的计算机科学界，从气候变化建模到洪水预测等领域的环境建模研究人员，以及与环境管理相关的关键利益相关者，我们包括来自该领域的一系列令人兴奋的合作机构，以最大限度地发挥这项工作的影响。

Cloud computing is one of the most important technological developments of the last few years, with the technology having a major and transformative impact on many areas of society and the economy. For example, cloud computing underpins developments in smart cities, ecommerce and eGovernment and also provides the storage and computational capabilities that underpin data science (cf. big data). The software support offered by cloud computing is however in its infancy and is tailored towards particular styles of application. This is particularly true with respect to computation in the cloud, where the programming approach offered by the computational framework MapReduce dominates and yet MapReduce assumes a particular style of programming where potentially massive data sets are analysed by a map() operation before results are collated through an associated reduce() operation. This is powerful but very limited.In parallel, researchers are also interested in realising the benefits of cloud computing in many other areas of application. This project focuses on the support offered by cloud computing to Environmental Science and, in particular, to the execution of potentially complex environmental models in the cloud. This is an area of huge significance, with environmental modelling being the key tool to evaluate uncertainty, risk assessment, and mitigation strategies around flood/ drought, food security and the impact of climate change (with major consequences for the economy and for society). We particularly focus on the principles and techniques in the key areas of Platform as a Service (or PaaS), effectively the middleware for cloud computing. The central insight is that services at the PaaS level need to be more carefully tailored to the needs of key application domains, including but not limited to support for the execution of complex environmental models. We advocate a novel approach based on a combination of model-driven engineering coupled with software frameworks and argue that this enables a paradigm shift in terms of the flexible and tailored support offered by cloud computing for given application domains.Key beneficiaries of this work include the computer science communities working on model-driven engineering and cloud computing, researchers from environmental modelling in areas ranging from climate change modellers to flood prediction, and also key stakeholders related to environmental management and we include an exciting range of partner institutions from this area to maximise the impact of this work.