CSR: Small: Reliability as a Service (RaaS) in Cloud Computing

尽管预计将转向云计算，但对云可靠性的高度关注仍然是私营和政府部门的首要问题，并敦促创新的解决方案来满足日益增长的不同可靠性要求的挑战。虽然现有技术允许云计算提供商向所有客户提供某种固定级别的可靠性，但它可能不足以或过于昂贵，无法满足他们的特定需求。该项目旨在开发一种新颖的框架，将可靠性作为一种弹性、透明的服务提供给云计算中的所有客户，这些服务可以定制和访问。该项目的目标是：(1)将两种可靠性方法（即检查点和复制）与效用优化进行整体集成，并适应具有异构用户需求的分布式云环境；(2)为云提供商制定定价方案，以将其？资源空白？使有利可图。这两个研究方向协同实现了可靠性即服务（RaaS）。随着按使用付费可靠性服务的引入，云计算客户可以根据每个特性选择他们需要的可靠性组件。只需一个复选框，就可以达到期望的可靠性水平。对于云服务提供商来说，RaaS为其服务提供了额外的收入和价值来源。通过构建现实的模型和开发资源分配、优化和定价的算法，该研究有望推动云计算艺术的开始。该项目还包括一个实施和实验部分，将产生关于最佳做法的宝贵知识，以及将结果转化为商业世界的主要障碍。该项目还将开展一系列涉及K-12、本科生和研究生的教育活动，并为招募和指导代表性不足的学生做出强有力的外展努力。

Despite a projected shift to cloud computing, heightened concerns over cloud reliability remain paramount in both private and government sectors, and urge innovative solutions to meet the growing challenge of disparate reliability requirements. While existing techniques allow cloud providers to offer some fixed level of reliability to all customers, it may be either inadequate or too expensive to fit their specific requirements. This project aims to develop a novel framework for providing reliability as an elastic, transparent service that can be customized and accessed by all customers in cloud computing. The goals of this project are: (1) holistic integration of two reliability approaches (viz., checkpointing and replication) with utility optimization and their adaptation to a distributed cloud environment with heterogeneous user demands, (2) the development of pricing schemes for cloud providers to put their ?resource white spaces? to profitable use. These two research directions collaboratively enable the realization of Reliability as a Service (RaaS). With the introduction of pay-per-use reliability services, cloud customers could choose reliability components they require on a feature-by-feature basis. Achieving a desired reliability level could be a single check box away. For cloud service providers, RaaS presents an additional source of revenue and value to their services. By constructing realistic models and developing algorithms for resource allocation and optimization and pricing, the proposed research is expected to advance the start of the art of cloud computing. The project also includes an implementation and experimental component that will yield valuable knowledge on best practices and the main obstacles towards transitioning the results into the commercial world. This project will also carry out a number of educational activities involving K-12, undergraduate, and graduate students, and make strong outreach efforts for recruiting and mentoring under-represented students.