SI2-SSE: AMASS - An Automated Monitoring AnalySis Service for Cyberinfrastructure

科学网关是社区开发的一组工具、应用程序和数据集合，它们通过门户或一套应用程序集成。它提供对超级计算机、软件工具和数据存储库的轻松访问（通常基于浏览器），使研究人员能够专注于他们的科学目标，而不是网络基础设施。这些门户正在促进来自大气科学、天体物理学、化学、生物物理学、生物化学、地震工程、地球物理学、神经科学和生物学等多个领域的数千名研究人员之间的合作和思想交流。然而，由于开发和管理人员资源有限，科学网关通常仅利用 NSF 资助的 CI 的一小部分来减轻大规模使用多种资源和服务所涉及的复杂性，部分原因是软件和硬件故障。由于许多成功的科学网关的用户基数空前增长，数据集不断增加，因此在不引入额外复杂性的情况下增加 CI 资源的使用将有助于他们满足这一需求。为了满足这一需求，将构建自动监测分析服务（AMASS），为最初专注于科学网关的监测数据的自动分析提供灵活且可扩展的服务。 AMASS将基于数据挖掘和机器学习技术以及新兴的大数据技术来分析监测数据，以提高CI的可靠性和运行效率以及系统和群体生物学、计算神经科学和生物物理学界的基本问题的进展。 将与 AMASS 一起构建一个模拟框架，用于测试自动分析算法和自适应执行技术。 将提供直观的查询 API 供科学网关软件使用，并将集成到以下三个目标科学网关中，以推动该项目的研究和开发：系统发育研究网络基础设施 (CIPRES)、神经科学网关 (NSG) 和 UltraScan。所提出的方法不需要对最终用户应用程序进行任何更改，并且软件开发将监控数据集成到其基础设施中以实现应用程序的自适应执行，从而显着提高科学网关的科学生产力和用户满意度，使科学家能够回答更复杂的问题，而无需了解大规模分布式环境的复杂性。开发的软件产品将作为 Apache 许可证下的开源产品提供，并将集成到 NSF 资助的 SciGap 项目中，以影响更广泛的科学网关。

A science gateway is a community-developed set of tools, applications, and data collections that are integrated via a portal or a suite of applications. It provides easy, typically browser-based, access to supercomputers, software tools, and data repositories to allow researchers to focus on their scientific goals and less on the cyberinfrastructure. These gateways are fostering collaboration and exchange of ideas among thousands of researchers from multiple communities ranging from atmospheric science, astrophysics, chemistry, biophysics, biochemistry, earthquake engineering, geophysics, to neuroscience, and biology. However due to limited development and administrative personnel resources, science gateways often leverage only a small subset of the NSF-funded CI to mitigate the complexities involved with using multiple resource and services at scale in part due to software and hardware failures. Since many successful science gateways have had unprecedented growth in their user base and ever increasing datasets, increasing their usage of CI resources without introducing additional complexity would help them meet this demand.In response to this need, an Automated Monitoring AnalySis Service (AMASS) will be built to provide a flexible and extensible service for automated analysis of monitoring data initially focused on science gateways. AMASS will be based on data mining and machine learning techniques and emerging big data technologies to analyze monitoring data for improving the reliability and operational efficiency of CI as well as progress on fundamental questions in systematic and population biology, computational neuroscience, and biophysics communities. Along with AMASS, a simulation framework will be built for testing automated analysis algorithms and adaptive execution techniques. An intuitive query API will be provided for science gateway software to use and will be integrated into the following three target science gateways that will drive the project's research and development: the Cyberinfrastructure for Phylogenetic Research (CIPRES), the Neuroscience Gateway (NSG), and UltraScan. The proposed approach does not require any changes to the end user applications, and the software developments will significantly enhance the science productivity and user satisfaction of science gateways by integrating monitoring data into their infrastructure to enable adaptive execution of their applications, allowing scientists to answer more sophisticated questions without having to understand the complexities of a large-scale distributed environment. The developed software products will be available as open source products under an Apache License and will be integrated into the NSF-funded SciGap project in order to impact a broader range of science gateways.