Network Measurement as a Service

服务器和网络虚拟化的最新进展催生了基础设施即服务范式，企业可以从云数据中心运营商那里租用资源，从而实现信息通信技术的外包。这些企业本身可以是应用程序和服务提供商，充当共享数据中心基础设施的租户。租户通过现收现付的定价模式调整其ICT业务，从而保持较低的资本（和运营）支出并提高利润率。这种基础设施抽象允许租户只关注他们的业务交付模型，而将基础设施维护留给运营商。然而，由于缺乏对底层基础设施动态状态的可见性，当其性能在短时间内波动时，可能会极大地损害租户的服务。这阻止了企业向云的更普遍迁移，而企业被迫维护自己的内部基础设施。雪上加霜的是，云计算中的安全风险更为严重。攻击者可以利用云服务器向其他租户发起DDoS攻击，或者利用更快的端口扫描来识别易受攻击的服务。特别是租户完全无法发现安全威胁，也无法在事件发生时自主采取补救措施。易受攻击的服务最终会消耗大量的计算和网络资源，给租户带来不可持续的账单，最终可能不得不从云计算中撤出他们的服务。现有的测量和监控方法是不够的，因为它们是专门为会计、流量工程或离线调试而设计的。来自这些方法的测量没有提供任何线索，说明应用程序是否遭受了自引起的拥塞或网络攻击，是否存在其他一些违规流/应用程序，或者由于某些交换机或应用程序组件的长队列延迟而导致的不可接受的延迟，以及有多少流受到它们的影响。虽然解决这些问题本身对云运营商来说很重要，但及时解决这些问题通常是不可能的，因为软件和硬件的更新需要时间，而且随着应用程序的发展，可能会出现新的病态流量模式。该项目的总体目标是设计和开发一个本地网络测量即服务（NMaaS）框架，该框架将允许租户表达他们的测量需求，并随后从简单的监视原语中合成相应的复杂服务级性能功能。所需的基本度量组件将在整个基础设施中需要的时间和地点动态透明地实例化，利用服务器和网络节点的临时可用容量。特别是，我们的目标是：-为流量监控设计新颖的服务器和交换机仪表功能，并使它们成为底层基础设施的原生部分，以便它们能够支持各种测量功能，同时减轻测量误差和不确定性-开发一个网络范围，通过在虚拟和物理网络组件中优化放置基于服务器和交换机的测量功能来综合复杂指标的集中编排算法-设计和开发测量需求描述api，以解析租户发布的高级测量规范并将其转换为低级测量指标。最终，我们的目标是证明所提议的框架将在维持预期的应用程序性能方面做出重大贡献，同时提高云资源的利用率。考虑到云计算仍然是一个快速增长的全球业务，我们预计研究结果将极大地惠及更广泛的IT行业。

Recent advances in server and network virtualisation have given rise to the Infrastructure-as-a-Service paradigm where businesses can lease resources from cloud datacentre operators, thus enabling the outsourcing of ICT. Such businesses can themselves be application and service providers who act as tenants of a shared data centre infrastructure. The tenants resize their ICT footprint through the pay-as-you-go pricing model, thereby maintaining low capital (and operational) expenditure and increasing their profit margin. This infrastructural abstraction allows tenants to focus solely on their business delivery model while leaving the infrastructure maintenance to the operators.However, the resulting lack of visibility to the dynamic state of the underlying infrastructure can immensely hurt the services of the tenants when its performance fluctuates in short timescales. This prohibits the more pervasive migration of businesses to the cloud who are instead forced to maintain their own, in-house infrastructures.Adding to the problem, security risks are more acute in the cloud. Attackers can leverage cloud servers to launch DDoS attacks to other tenants or faster portscan to identify vulnerable services. Especially tenants are completely excluded from detecting security threats and from taking remedial action autonomously as the incidents unfold. Vulnerable services can end up consuming immense amounts of compute and network resources, leading to unsustainable bills for tenants who ultimately may have to retreat their services from the cloud. Existing measurement and monitoring approaches are inadequate because they are architected specifically for accounting, traffic engineering or offline debugging. Measurements from these approaches provide no clue on whether an application suffers self-induced congestion or cyber-attacks, there are some other offending flows/applications, or unacceptable latencies are due to long queueing delay at certain switch or application components, and how many flows are impacted by them. While addressing these problems itself is important to cloud operators, doing so in a timely fashion is often simply impossible because software and hardware updates take time and new pathological traffic patterns may arise as applications evolve.The overarching goal of this project is to design and develop a native Network Measurement-as-a-Service (NMaaS) framework that will allow tenants to express their measurement needs, and to subsequently synthesise the corresponding complex service-level performance functions out of simple monitoring primitives. The required primitive measurement components will be dynamically and transparently instantiated when and where required throughout the infrastructure, exploiting the temporal available capacity of servers and network nodes. In particular, we aim to:- devise novel server and switch instrumentation capabilities for traffic monitoring and make them as a native part of an underlying infrastructure so that they can support diverse measurement functions while alleviating measurement errors and uncertainties- develop a network-wide, centrally-orchestrated algorithm for the synthesis of complex metrics through the optimal placement of server-based and switch-based measurement functions in virtual and physical network components- design and develop measurement requirement description APIs to parse high-level measurement specifications issued by tenants and transform them into low-level measurement indicators.Ultimately, we aim to demonstrate that the proposed framework will contribute significantly in maintaining the desired application performance while at the same time improving the utilisation of cloud resources. Given that the cloud is still a rapidly growing global business, we anticipate that the research outcome will greatly benefit the wider IT industry.