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

尽管预计将转向云计算，但对云计算可靠性的高度关注仍然是私营部门和政府部门的首要任务，并敦促创新解决方案以满足日益增长的不同可靠性要求的挑战。虽然现有的技术允许云提供商为所有客户提供某种固定的可靠性水平，但它可能不足以满足客户的特定需求，或者过于昂贵。该项目旨在开发一种新的框架，以提供可靠性作为弹性，透明的服务，可以定制和访问的所有客户在云计算。该项目的目标是：（1）两种可靠性方法（即，检查点和复制）与实用程序优化和适应分布式云环境与异构用户的需求，（2）定价方案的发展，云提供商把他们的？资源白色空间？有利可图的使用。这两个研究方向共同实现了可靠性即服务（RaaS）。随着按使用付费的可靠性服务的引入，云客户可以按功能选择他们所需的可靠性组件。实现所需的可靠性水平可能是一个单一的复选框。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算法的资源分配和优化和定价，所提出的研究预计将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和将成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宣传努力。

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.