论文标题
建模混合云经纪的操作公平性
Modeling Operational Fairness of Hybrid Cloud Brokerage
论文作者
论文摘要
云服务经纪是一项新兴技术,试图简化混合云的消耗和运行。当今的云经纪人试图使消费者与多个云的变化造成隔离度。为了实现隔热材料,现代云经纪人需要通过创建和操作虚拟数据中心结构和我们称为元云的虚拟数据中心结构来掩饰自己为消费者的最终产品,该构造是在一组参与的供应商云之上组装的。对于云消费者和基础云供应商而言,这样的云经纪人将被视为可信赖的合作伙伴至关重要。经纪信托的基本宗旨是供应商中立。一方面,如果云经纪人保证不会通过首选路径带领他们,云消费者将感到舒适。另一方面,云供应商将对与云经纪人合作更感兴趣,云经纪人承诺对客户提供请求进行公平分配。由于消费者和供应商对元云经纪人的信任是源于对供应商云的不可知论的假设,因此需要一种测试策略来验证云经纪的公平性。在本文中,我们提出了一个公平的演算,该计算定义了确定云代理的操作行为的规则。微积分使用时间逻辑来模拟公平性是必须随着时间时间确定的特征的事实。这不是一个可以在每次要求履行级别上判断的特征。我们使用我们的公平性计算作为基础,我们提出了一种算法,以根据其观察到的要求分配策略来确定经纪人概率的公平性。我们关于云代理行为公平性的模型也因成本差异和容量差异等管理变量的因素而发生。
Cloud service brokerage is an emerging technology that attempts to simplify the consumption and operation of hybrid clouds. Today's cloud brokers attempt to insulate consumers from the vagaries of multiple clouds. To achieve the insulation, the modern cloud broker needs to disguise itself as the end-provider to consumers by creating and operating a virtual data center construct that we call a meta-cloud, which is assembled on top of a set of participating supplier clouds. It is crucial for such a cloud broker to be considered a trusted partner both by cloud consumers and by the underpinning cloud suppliers. A fundamental tenet of brokerage trust is vendor neutrality. On the one hand, cloud consumers will be comfortable if a cloud broker guarantees that they will not be led through a preferred path. And on the other hand, cloud suppliers would be more interested in partnering with a cloud broker who promises a fair apportioning of client provisioning requests. Because consumer and supplier trust on a meta-cloud broker stems from the assumption of being agnostic to supplier clouds, there is a need for a test strategy that verifies the fairness of cloud brokerage. In this paper, we propose a calculus of fairness that defines the rules to determine the operational behavior of a cloud broker. The calculus uses temporal logic to model the fact that fairness is a trait that has to be ascertained over time; it is not a characteristic that can be judged at a per-request fulfillment level. Using our temporal calculus of fairness as the basis, we propose an algorithm to determine the fairness of a broker probabilistically, based on its observed request apportioning policies. Our model for the fairness of cloud broker behavior also factors in inter-provider variables such as cost divergence and capacity variance.