On Achieving High Survivability in Virtualized Data Centers

Abstract

SUMMARYAs businesses are increasingly relying on the cloud to host their services, cloud providers are striving to offer guaranteed and highlyavailable resources. To achieve this goal, recent proposals have advocated to offer both computing and networking resources in the form of Virtual Data Centers (VDCs). Subsequently, several attempts have been made to improve the availability of VDCs through reliability-aware resource allocation schemes and redundancy provisioning techniques. However, the research to date has not considered the heterogeneity of the underlying physical components. Specifically, it does not consider recent findings showing that failure rates and availability of data center equipments can vary significantly depending on various parameters including their types and ages. To address this limitation, in this paper we propose a High-availability Virtual Infrastructure management framework (Hi-VI) that takes into account the heterogeneity of cloud data center equipments to dynamically provision backup resources in order to ensure required VDC availability. Specifically, we propose a technique to compute the availability of a VDC that considers both (1) the heterogeneity of data center networking and computing equipments in terms of failure rates and availability, and (2) the number of redundant virtual nodes and links provisioned as backups. We then leverage this technique to propose an allocation scheme that jointly provisions resources for VDCs and backups of virtual components with the goal of achieving the required VDC availability while minimizing energy costs.Through simulations, we demonstrate the effectiveness of our framework compared to heterogeneity-oblivious solutions.

On the Optimal Approach of Survivable Virtual Network Embedding in Virtualized SDN

“…Virtualization technology have drawn great attention in recent years, and many virtual network embedding (VNE) problems as well as solutions have also been studied extensively [8]- [10]. Meanwhile, the technology of VN is evolving with the development of cloud datacenter network and SDN.…”

“…When virtual network requests arrive, the requested vswitches are sorted in descending order, which is similar to physical network nodes (lines 3-4). And then, the largest weight of virtual switch of virtual network request will be mapped to the largest weight nodes of physical network (lines [5][6][7][8][9][10][11][12][13][14]. All the virtual nodes, which are included in VNR, will try to be mapped.…”

Algorithms for advance bandwidth reservation in media production networks

“…In particular, the efficiency and applicability of containers needs to be studied more, just like there is need to study and propose more efficient function scheduling algorithms. In addition, given the dynamic requirements of NFV, there is need for resource allocation proposals that are able to find solutions online, consider multi-domain and distributed VNFs [179], [180], network survivability [181], dynamic resource management [182] etc.…”

LIVE: Learning and Inference for Virtual Network Embedding

“…Amokrane et al [41] proposed a holistic resource management framework to embed Virtual Data Centers across geographically distributed Data Centers connected through a backbone network. Rabbani et al [42] took the heterogeneity of Data Center equipment into account and proposed an embedding algorithm that jointly provisioned resources and backups. Different from the above literatures, our novel LIVE algorithm explores the relationships between the mapped VN requests and the mapping ones from a statistical perspective, for the first time in the VNE problem.…”