CiC: Science of Cloud-Scale Computing

康奈尔大学致力于打造一门高可靠的云计算科学。需要这样的科学来支持敏感的计算应用程序，这些应用程序需要比现代云平台的典型保证更高的保证程度，例如在安全性、隐私、一致性、容错或响应保证方面。康奈尔大学的研究小组正在使用一个三管齐下的方法：1.量化当今S云平台的特性的实验。2.今天运行的软件解决方案？S云，但增强了它们的性能。这需要协议和系统的设计、实现和评估，但也将涉及创建模型和证据，为未来高度可靠的云计算科学做出贡献。随着这些新工具的出现，该团队可以通过使用它们在选定领域(金融、医疗保健、智能电网控制)中创建关键应用程序的原型，重新评估其性能，然后探索所需的优化和增强以支持实际应用程序工作负载，从而重新启动周期。对Microsoft Azure的深入访问使团队能够创建对Azure用户具有即时实用价值的知识体系。然而，通过努力为高度可靠的云计算奠定更深层次的科学基础，人们期望任何关键的见解都将同样适用于非微软系统。

Cornell effort works towards a science of high-assurance cloud computing. Such a science is needed for to support sensitive computing applications that require higher degrees of assurance than is typical for modern cloud platforms, for example in their security, privacy, consistency, fault-tolerance or responsiveness guarantees. The Cornell group is using a three-pronged approach: 1. Experiments to quantify the properties of today?s cloud platforms. 2. Software solutions that run on today?s clouds but enhance their properties. This entails protocol and system design, implementation, and evaluation, but will also involve creating models and proofs contributing towards a future science of highly assured cloud computing.3. As these new tools emerge, the group can restart the cycle by using them to prototype critical applications in selected domains (finance, healthcare, control of the smart power grid), reevaluate their performance, and then explore needed optimizations and enhancements to support realistic application workloads.Intensive access to Microsoft Azure permits the team to create a body of knowledge with immediate practical value for Azure users. However, by working towards a deeper scientific foundation for highly assured cloud computing, the expectation is that any key insights will be equally applicable on non-Microsoft systems.