Abstract-The increasing popularity of Cloud Computing is leading to the emergence of large virtualized data centers hosting increasingly complex and dynamic IT systems and services. Over the past decade, the efficient sharing of computational resources through virtualization has been subject to intensive research, while network management in cloud data centers has received less attention. A variety of network-intensive applications require QoS (Quality-of-Service) provisioning, performance isolation and support for flexible and efficient migration of virtual machines. In this paper, we survey existing network virtualization approaches and evaluate the extent to which they can be used as a basis for realizing the mentioned requirements in a cloud data center. More specifically, we identify generic network virtualization techniques, characterize them according to their features related to QoS management and performance isolation, and show how they can be composed together and used as building blocks for complex network virtualization solutions. We then present an overview of selected representative cloud platforms and show how they leverage the generic techniques as a basis for network resource management. Finally, we outline open issues and research challenges in the area of performance modeling and proactive resource management of virtualized data center infrastructures.
In this paper, we address the problem of performance analaysis in computer networks. We present a new meta-model designed for the performance modeling of network infrastructures in modern data centers. Instances of our metamodel can be automatically transformed into stochastic simulation models for performance prediction. We evaluate the approach in a case study of a road traffic monitoring system. We compare the performance prediction results against the real system and a benchmark. The presented results show that our approach, despite of introducing many modeling abstractions, delivers predictions with errors less than 32% and correctly detects bottlenecks in the modeled network.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.