Analysis and Optimization of the Trade-off between QoE and Energy-Efficiency in Data centers

数据中心的节能运行越来越受到人们的关注。然而，节能通常会导致可用计算资源的退化，从而导致服务质量（QoS）的降低。降低的QoS反过来会导致终端用户的体验质量（QoE）变差。虽然已经有几种方法解决了数据中心的优化问题，以确保能源效率或解决某些QoS约束，但没有研究这两个目标的联合优化。此外，QoE应该能够全面理解网络通信系统的定性性能，从而补充传统的、更以技术为中心的QoS观点。该项目侧重于量化和调整数据中心QoE和能源效率之间的权衡。我们考虑了虚拟桌面基础设施（vdi）的用例，它被认为在接下来的几年里会产生越来越大的影响。VDI使用户能够使用非常轻量级的系统，即所谓的瘦客户机，从而实际的操作系统在数据中心中运行。这种方法可以通过更好地利用数据中心的现有资源来实现规模经济，从而节省成本和能源。但是，如果将太多的服务聚合到非常少的服务器上，则无法满足服务需求，或者导致处理时间显著增加。因此，QoS和QoE都会受到影响。另外的挑战出现了，因为vdi为用户提供了一个完整的操作系统，包括各种不同需求的应用程序，例如Office产品。该项目旨在根据vdi内部运行的应用程序类型的功能和对客户端设备、传输网络和数据中心的可能需求进行分类。VDI环境中特定应用程序类的详细QoE模型将基于主观用户研究（例如通过众包）派生出来。这种QoE模型量化了终端用户QoE与整个传输链中包括客户端、网络端和数据中心端的不同影响因素之间的关系。同时，在现有研究的基础上，定义相应的数据中心能耗模型。假设整个传输链上的所有信息都是可用的，这允许通过调整（例如，服务请求的调度、服务器的冷热备用或虚拟机（VM）的放置方法）来获得QoE和能效之间的最佳权衡。拟议项目中使用的方法结合了文献研究、基于专用测试平台的测量、以及使用离散事件模拟和分析方法（如排队论）的优化方法的主观用户研究。本提案所述的工作将与越南河内科技大学合作完成

Energy-efficient operation of data centers is gaining more and more attention. However, saving energy usually leads to a degradation of the available computing resources, which results in reduced Quality of Service (QoS). The diminished QoS can in turn lead to poor Quality of Experience (QoE) for the end-users. Although several approaches already address the optimization of data centers either to ensure energy-efficiency or to resolve certain QoS constraints, the joint optimization of both objectives is not researched. Furthermore, QoE is supposed to enable a holistic understanding of the qualitative performance of networked communication systems and thus to complement the traditional, more technology-centric QoS perspective.This project focuses on quantifying and adjusting the trade-off between QoE and energy-efficiency in data centers. We consider the use case of Virtual Desktop Infrastructures (VDIs) that are considered to have an increasing impact in the following years. A VDI enables users to use very lightweight systems, so-called thin clients, whereby the actual operating system runs in a data center. This approach may lead to cost and energy savings due to economies of scale by better utilization of existing resources in the data center. However, if too many services are aggregated onto very few servers, the service requirements cannot be fulfilled or result in significantly increased processing times. As a result, QoS and therefore QoE suffers. Additional challenges arise, as VDIs provide the user an entire operating system including various applications, e.g. Office products, with different requirements. The project aims at classifying the application types running inside VDIs according to their functionality and possible requirements on the client device, transmission network, and data center. Detailed QoE models for specific application-classes in a VDI environment will be derived based on subjective user studies e.g. via crowdsourcing. Such a QoE model quantifies the relation between the end-user QoE and different influence factors on the entire transmission chain including the client, network, and data center side. In parallel, corresponding models for the energy-consumption in data centers will be defined based on existing studies. Assuming that all information on the entire transmission chain is available, this allows for deriving the optimal trade-off between QoE and energy-efficiency by adjusting, e.g., scheduling of service requests, hot and cold stand-by of servers or virtual machine (VM) placement approaches.The methodology used in the proposed project combines literature studies, measurements based on dedicated testbeds, and subjective user studies with optimization methods using discrete-event simulations and analytical methods, like queuing theory. The work described in this proposal will be done in collaboration with the Hanoi University of Science and Technology, Vietnam