Gregor Schaffrath

Bio: Gregor Schaffrath is an academic researcher from Technical University of Berlin. The author has contributed to research in topics: Competitive analysis & Heuristic (computer science). The author has an hindex of 2, co-authored 2 publications receiving 61 citations.

Competitive analysis for service migration in VNets

Abstract: Network virtualization promises a high flexibility by decoupling services from the underlying substrate network and allowing the virtual network to adapt to the needs of the service, e.g., by migrating servers or/and parts of the network. We study a system (e.g., a gaming application) where network virtualization is used to support thin client applications for mobile devices to improve their QoS. To deal with the dynamics of both the mobile clients as well as the ability to migrate services closer to the client location we advocate, in this paper, the use of competitive analysis. After identifying the parameters that characterize the cost-benefit tradeoff for this kind of application we propose an online migration strategy. The strength of the strategy is that it is robust with regards to any arbitrary request access pattern. In particular, it is close to the optimal offline algorithm that knows the access pattern in advance.In this paper we present both an optimal offline algorithm based on dynamic programming techniques to find the best migration paths for a given request sequence, and a O(¼ log n)-competitive migration strategy MIG where ¼ is the ratio between maximal and minimal link capacity in the substrate network for a simplified model. This is almost optimal for small ¼, as we also show that there are networks where no online algorithm can achieve a ratio below ©(log n/log log n). In contrast, the optimal solution without migration can only achieve a competitive ratio that is linear in the network diameter. Our simulations indicate that the competitive ratio of MIG is robust to the network size, and that the ratio is small if the request dynamics are limited and the requests are correlated.

Generalized and Resource-Efficient VNet Embeddings with Migrations

Abstract: This paper attends to the problem of embedding flexibly specified CloudNets, virtual networks connecting cloud resources (such as storage or computation). We attend to a scenario where customers can request CloudNets at short notice, and an infrastructure provider (or a potential itermediate broker or reseller) first embeds the CloudNet fast (e.g., using a simple heuristic). Later, however, long-lived CloudNets embeddings are optimized by migrating them to more suitable locations, whose precise definition depends on a given objective function. For instance, such migrations can be useful to reduce the peak resource loads in the network by spreading CloudNets across the infrastructure, to save energy by moving CloudNets together and switching off unused components, or for maintenance purposes. We present a very generic algorithm to compute optimal embeddings of CloudNets: It allows for different objective functions (such as load minimization or energy conservation), supports cost-aware migration, and can deal with all link types that arise in practice (e.g., full-duplex or even wireless or wired broadcast links with multiple endpoints). Our evaluation shows that such a rigorous optimization is even feasible in order to optimize a moderate-size CloudNet of full flexibility (e.g., a router site, a small physical infrastructure or virtual provider network).

Virtual Network Embedding: A Survey

Abstract: Network virtualization is recognized as an enabling technology for the future Internet. It aims to overcome the resistance of the current Internet to architectural change. Application of this technology relies on algorithms that can instantiate virtualized networks on a substrate infrastructure, optimizing the layout for service-relevant metrics. This class of algorithms is commonly known as "Virtual Network Embedding (VNE)" algorithms. This paper presents a survey of current research in the VNE area. Based upon a novel classification scheme for VNE algorithms a taxonomy of current approaches to the VNE problem is provided and opportunities for further research are discussed.

Resource Discovery and Allocation in Network Virtualization

Abstract: Network virtualization is considered an important potential solution to the gradual ossification of the Internet. In a network virtualization environment, a set of virtual networks share the resources of a common physical network although each virtual network is isolated from others. Benefits include increased flexibility, diversity, security and manageability. Resource discovery and allocation are fundamental steps in the process of creating new virtual networks. This paper surveys previous work on, and the present status of, resource discovery and allocation in network virtualization. We also describe challenges and suggest future directions for this area of research.

Virtual Network Embedding with Opportunistic Resource Sharing

Abstract: Network virtualization has emerged as a promising approach to overcome the ossification of the Internet. A major challenge in network virtualization is the so-called virtual network embedding problem, which deals with the efficient embedding of virtual networks with resource constraints into a shared substrate network. A number of heuristics have been proposed to cope with the NP-hardness of this problem; however, all of the existing proposals reserve fixed resources throughout the entire lifetime of a virtual network. In this paper, we re-examine this problem with the position that time-varying resource requirements of virtual networks should be taken into consideration, and we present an opportunistic resource sharing-based mapping framework, ORS, where substrate resources are opportunistically shared among multiple virtual networks. We formulate the time slot assignment as an optimization problem; then, we prove the decision version of the problem to be NP-hard in the strong sense. Observing the resemblance between our problem and the bin packing problem, we adopt the core idea of first-fit and propose two practical solutions: first-fit by collision probability (CFF) and first-fit by expectation of indicators' sum (EFF). Simulation results show that ORS provides a more efficient utilization of substrate resources than two state-of-the-art fixed-resource embedding schemes.

A Path Generation Approach to Embedding of Virtual Networks

Abstract: As the virtualization of networks continues to attract attention from both industry and academia, the virtual network embedding (VNE) problem remains a focus of researchers. This paper proposes a one-shot, unsplittable flow VNE solution based on column generation. We start by formulating the problem as a path-based mathematical program called the primal, for which we derive the corresponding dual problem. We then propose an initial solution which is used, first, by the dual problem and then by the primal problem to obtain a final solution. Unlike most approaches, our focus is not only on embedding accuracy but also on the scalability of the solution. In particular, the one-shot nature of our formulation ensures embedding accuracy, while the use of column generation is aimed at enhancing the computation time to make the approach more scalable. In order to assess the performance of the proposed solution, we compare it against four state of the art approaches as well as the optimal link-based formulation of the one-shot embedding problem. Experiments on a large mix of virtual network (VN) requests show that our solution is near optimal (achieving about 95% of the acceptance ratio of the optimal solution), with a clear improvement over existing approaches in terms of VN acceptance ratio and average substrate network (SN) resource utilization, and a considerable improvement (92% for a SN of 50 nodes) in time complexity compared to the optimal solution.