CiC: Science of Cloud-Scale Computing

康奈尔大学致力于发展一门高保证的云计算科学。需要这样一门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更高程度的保证，例如在安全性、隐私性、一致性、容错性或响应性保证方面。康奈尔大学的研究小组采用了三管齐下的方法：用实验来量化今天的属性？S云平台。2. 今天运行的软件解决方案？S云，但增强其性质。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明，为高度可靠的云计算的未来科学做出贡献。随着这些新工具的出现，该小组可以重新启动这个周期，使用它们在选定的领域（金融、医疗保健、智能电网控制）中对关键应用程序进行原型设计，重新评估其性能，然后探索所需的优化和增强，以支持实际的应用程序工作负载。对Microsoft Azure的密集访问使团队能够为Azure用户创建具有即时实用价值的知识体系。然而，通过为高度可靠的云计算提供更深入的科学基础，我们期望任何关键的见解都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.