Efficient, Scalable and Survivable Design for next generation Virtualized Data Center for Cloud Services

随着大型和小型组织开始利用云计算带来的好处，云计算正在成为主流范式。云计算之所以获得成功，是因为它提供了IT所需要的东西：能够以经济有效的方式随时随地增加和缩减计算资源，而无需设计和设置基础设施。使计算需求适应市场波动的能力只是云计算必须提供的众多好处之一，这就是这种新范式迅速崛起的原因。根据Gartner的一份报告，2013年全球云服务预计将增长到1310亿美元。随着这种大规模的增长，基础设施的性能对其成功和可持续性至关重要。目前，云计算在很大程度上依赖于数据中心来满足其日常业务需求。事实上，正是通过数据中心的虚拟化，“作为实用工具的计算”的概念才得以出现。然而，数据中心虚拟化仍处于起步阶段。最近，NSERC创建了一个虚拟基础设施智能应用战略网络（SAVI），其目标是解决建立在灵活和可发展的基础设施上的未来应用平台的设计。SAVI的目标之一是通过积极参与研究计划，加强信息技术（IT）工业基础，帮助推进加拿大的数字经济战略。这项倡议强调了云网络和网络虚拟化研究的重要性，以及它们将对加拿大工业产生的影响。然而，通过这一举措，可以确定与数据中心虚拟化相关的大量开放研究问题和挑战，包括但不限于优化拓扑和协议，嵌入设计方法和在线算法，资源供应和分配，数据中心能源效率，级联相关故障的容错问题和容错设计，提高灾难性灾难条件下的服务可用性等。

Cloud Computing is becoming the mainstream paradigm, as organizations, both large and small, begin to harness benefits. Cloud computing gained its success for giving IT exactly what it needed: The ability to grow and shrink computing resources, on the go, in a cost-effective manner, without the anguish of infrastructure design and setup. The ability to adapt computing demands to market fluctuations is just one of the many benefits that cloud computing has to offer, this is why this new paradigm is rising rapidly. According to a Gartner report, cloud services are expected to grow to 131 billion dollars worldwide in 2013. With this massive growth, the performance of the underlying infrastructure is crucial to its success and sustainability. Currently, cloud computing heavily depends on data centers for its daily business needs. In fact, it is through the virtualization of data centers that the concept of “computing as a utility” emerged. However, data center virtualization is still in its infancy. Recently, NSERC has created a Strategic Network for Smart Applications on Virtual Infrastructure (SAVI) whose objective is to address the design of future applications platform built on a flexible and evolvable infrastructure. Among SAVI’s objectives is helping advance Canada's Digital Economy Strategy by strengthening the IT (Information Technology) industrial base through active participation in the research program. This initiative underscores the importance of research on cloud networks and network virtualization and the impacts they will have on Canadian industries. With this initiative, however, a plethora of open research issues and challenges related to data center virtualization can be identified, including but not limited to, optimized topologies and protocols, embedding design methods and online algorithms, resource provisioning and allocation, data center energy efficiency, fault tolerance issues and fault tolerant design for cascaded correlated failures, improving service availability under catastrophic disaster conditions, etc. Therefore, this proposal will attempt to elaborate and address key research challenges and problems related to the design and operation of efficient virtualized data centers and data center infrastructure for cloud services. In particular, I plan to investigate the problem of scalable traffic management and traffic engineering methods in data center networks and present both mathematical formulation for the (offline) problem as well as online methods/algorithms to enable quality of service (QoS) provisioning. I also plan to study the problem of survivable virtual network embedding through novel coordinated design methodologies to achieve higher revenues for network operators while providing guaranteed service continuity for cloud services. Given the complexity of this problem, we plan to use large scale optimization methods for addressing the offline design problem and novel algorithms for obtaining online solutions. Now, one of the major issues for network operators is to maximize their profits; this implies squeezing the most benefits of their network investments and capacity to be able to accommodate more services. Network coding is a framework that allows network operators to maximize the traffic flows in their network without requiring any upgrade to the infrastructure. To get the most benefits, network coding aware embedding solutions must be devised. This is however another challenging problem that has not been addressed in prior work. This proposal plans to investigate this problem through novel embedding solutions as well as offline and online methods to characterize the gains.