Survivable Virtual Infrastructure Mapping in Virtualized Data Centers

In a virtualized data center, survivability can be enhanced by creating redundant VMs as backup for VMs such that after VM or server failures, affected services can be quickly switched over to backup VMs. To enable flexible and efficient resource management, we propose to use a service-aware approach in which multiple correlated Virtual Machines (VMs) and their backups are grouped together to form a Survivable Virtual Infrastructure (SVI) for a service or a tenant. A fundamental problem in such a system is to determine how to map each SVI to a physical data center network such that operational costs are minimized subject to the constraints that each VM’s resource requirements are met and bandwidth demands between VMs can be guaranteed before and after failures. This problem can be naturally divided into two sub-problems: VM Placement (VMP) and Virtual Link Mapping (VLM). We present a general optimization framework for this mapping problem. Then we present an efficient algorithm for the VMP subproblem as well as a polynomial-time algorithm that optimally solves the VLM subproblem, which can be used as subroutines in the framework. We also present an effective heuristic algorithm that jointly solves the two subproblems. It has been shown by extensive simulation results based on the real VM data traces collected from the green data center at Syracuse University that compared with the First Fit Descending (FFD) and single shortest path based baseline algorithm, both our VMP+VLM algorithm and joint algorithm significantly reduce the reserved bandwidth, and yield comparable results in terms of the number of active servers

Resource Management in Virtualized Data Center

As businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highly-available resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). However, to offer VDCs, cloud providers have to overcome several technical challenges. In this thesis, we focus on two key challenges: (1) the VDC embedding problem: how to efficiently allocate resources to VDCs such that energy costs and bandwidth consumption are minimized, and (2) the availability-aware VDC embedding and backup provisioning problem which aims at allocating resources to VDCs with hard guarantees on their availability. The first part of this thesis is primarily concerned with the first challenge. The goal of the VDC embedding problem is to allocate resources to VDCs while minimizing the bandwidth usage in the data center and maximizing the cloud provider's revenue. Existing proposals have focused only on the placement of VMs and ignored mapping of other types of resources like switches. Hence, we propose a new VDC embedding solution that explicitly considers the embedding of virtual switches in addition to virtual machines and communication links. Simulations show that our solution results in high acceptance rate of VDC requests, less bandwidth consumption in the data center network, and increased revenue for the cloud provider. In the second part of this thesis, we study the availability-aware VDC embedding and backup provisioning problem. The goal is to provision virtual backup nodes and links in order to achieve the desired availability for each VDC. Existing solutions addressing this challenge have overlooked the heterogeneity of the data center equipment in terms of failure rates and availability. To address this limitation, we propose a High-availability Virtual Infrastructure (Hi-VI) management framework that jointly allocates resources for VDCs and their backups while minimizing total energy costs. Hi-VI uses a novel technique to compute the availability of a VDC that considers both (1) the heterogeneity of the data center networking and computing equipment, and (2) the number of redundant virtual nodes and links provisioned as backups. Simulations demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions in terms of revenue and the number of physical servers used to embed VDCs

Resilience options for provisioning anycast cloud services with virtual optical networks

Optical networks are crucial to support increasingly demanding cloud services. Delivering the requested quality of services (in particular latency) is key to successfully provisioning end-to-end services in clouds. Therefore, as for traditional optical network services, it is of utter importance to guarantee that clouds are resilient to any failure of either network infrastructure (links and/or nodes) or data centers. A crucial concept in establishing cloud services is that of network virtualization: the physical infrastructure is logically partitioned in separate virtual networks. To guarantee end-to-end resilience for cloud services in such a set-up, we need to simultaneously route the services and map the virtual network, in such a way that an alternate routing in case of physical resource failures is always available. Note that combined control of the network and data center resources is exploited, and the anycast routing concept applies: we can choose the data center to provide server resources requested by the customer to optimize resource usage and/or resiliency. This paper investigates the design of scalable optimization models to perform the virtual network mapping resiliently. We compare various resilience options, and analyze their compromise between bandwidth requirements and resiliency quality

Survivable Virtual Network Redesign and Embedding in Cloud Data Center Networks

Today, the cloud computing paradigm enables multiple virtualized services to co- exist on the same physical machine and share the same physical resources, hard- ware, as well as energy consumption expenses. To allow cloud customers migrate their services on to the cloud side, the Infrastructure Provider (InP) or cloud data centre operator provisions to its tenants virtual networks (VNs) to host their services. Virtual Networks can be thought of as segmenting the physical net- work and its resources, and such VN requests (or tenants) need to be mapped onto the substrate network and provisioned with sufficient physical resources as per the users’ requirements. With this emerging computing paradigm, cloud cus- tomers may demand to have highly reliable services for the hosted applications; however, failures often happen unexpectedly in data-centers, interrupting critical cloud services. Consequently, VN or cloud services are provisioned with redun- dant resources to achieve the demanded level of service reliability. To maintain a profitable operation of their network and resources, and thus achieve increased long term revenues, cloud network operators often rely on optimizing the map- ping of reliable cloud services. Such problem is referred to as in the literature as “Survivable Virtual Network Embedding (SVNE) ” problem. In this thesis, the survivable VN embedding problem is studied and a novel cost-efficient Survivable Virtual Network Redesign algorithm is carefully designed, presented, and evalu- ated. Subsequently, we distinguish between the communication services provided by the cloud provider and study the problem of survivable embedding of multicast services; we formally model the problem, and present two algorithms to reactively maintain multicast trees in cloud data centers upon failures