Network virtualization is a technology of running multiple heterogeneous network architecture on a shared substrate network. One of the crucial components in network virtualization is virtual network embedding, which provides a way to allocate physical network resources (CPU and link bandwidth) to virtual network requests. Despite significant research efforts on virtual network embedding in wired and cellular networks, little attention has been paid to that in wireless multi-hop networks, which is becoming more important due to its rapid growth and the need to share these networks among different business sectors and users. In this paper, we first study the root causes of new challenges of virtual network embedding in wireless multi-hop networks, and propose a new embedding algorithm that efficiently uses the resources of the physical substrate network. We examine our algorithm's performance through extensive simulations under various scenarios. Due to lack of competitive algorithms, we compare the proposed algorithm to five other algorithms, mainly borrowed from wired embedding or artificially made by us, partially with or without the key algorithmic ideas to assess their impacts.
Related work on embedding in wired networks mainly focuses on addressing computational challenges by restricting the problem space in different dimensions or proposing heuristic algorithms @cite_8 @cite_3 @cite_12 . For example, only bandwidth requirements are considered in @cite_8 @cite_3 or all VN requests are assumed to be given in advance @cite_3 @cite_9 . The authors in @cite_8 @cite_3 @cite_9 also considered the substrate network with infinite capacity, accepting all incoming VN requests. On embedding problems over SN with limited resources, multicommodity flow detection based algorithms are proposed in @cite_13 @cite_2 , where node embedding methods also consider their relation to the link embedding stage like our work. However, all algorithms in @cite_3 @cite_9 @cite_13 @cite_2 separate node and link embedding process, , all VN nodes are embedded before embedding the VN links. A single-stage wired embedding algorithm is also proposed in @cite_18 which tries to find a subgraph isomorphism of the VN via a method. There, the algorithm imposes a limit on the length of substrate paths that will embed virtual links and checks feasibility whenever a new VN link is embedded: if it is infeasible, it is backtracked to the last feasible embedding.
@cite_18 @cite_8 @cite_9 @cite_3 @cite_2 @cite_13 @cite_12
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A key challenge in network virtualization is to efficiently map a virtual network (VN) on a substrate network (SN), while accounting for possible substrate failures. This is known as the survivable VN embedding (SVNE) problem. The state-of-the-art literature has studied the SVNE problem from infrastructure providers’ (InPs’) perspective, i.e., provisioning backup resources in the SN. A rather unexplored solution spectrum is to augment the VN with sufficient spare backup capacity to survive substrate failures and embed the resulting VN accordingly. Such augmentation enables InPs to offload failure recovery decisions to the VN operator, thus providing more flexible VN management. In this paper, we study the problem of jointly optimizing spare capacity allocation in a VN and embedding the VN to guarantee full bandwidth in the presence of multiple substrate link failures. We formulate the optimal solution to this problem as a quadratic integer program that we transform into an integer linear program. We also propose a heuristic algorithm to solve larger instances of the problem. Based on analytical study and simulation, our key findings are: 1) provisioning shared backup resources in the VN can yield 33 more resource efficient embedding compared to doing the same at the SN level and 2) our heuristic allocates 21 extra resources compared to the optimal, while executing several orders of magnitude faster. Network virtualization allows multiple heterogeneous virtual networks (VNs) to coexist on a shared infrastructure. Efficient mapping of virtual nodes and virtual links of a VN request onto substrate network resources, also known as the VN embedding problem, is the first step toward enabling such multiplicity. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms that had clear separation between the node mapping and the link mapping phases. In this paper, we present ViNEYard-a collection of VN embedding algorithms that leverage better coordination between the two phases. We formulate the VN embedding problem as a mixed integer program through substrate network augmentation. We then relax the integer constraints to obtain a linear program and devise two online VN embedding algorithms D-ViNE and R-ViNE using deterministic and randomized rounding techniques, respectively. We also present a generalized window-based VN embedding algorithm (WiNE) to evaluate the effect of lookahead on VN embedding. Our simulation experiments on a large mix of VN requests show that the proposed algorithms increase the acceptance ratio and the revenue while decreasing the cost incurred by the substrate network in the long run. Recently network virtualization has been proposed as a promising way to overcome the current ossification of the Internet by allowing multiple heterogeneous virtual networks (VNs) to coexist on a shared infrastructure. A major challenge in this respect is the VN embedding problem that deals with efficient mapping of virtual nodes and virtual links onto the substrate network resources. Since this problem is known to be NP-hard, previous research focused on designing heuristic-based algorithms which had clear separation between the node mapping and the link mapping phases. This paper proposes VN embedding algorithms with better coordination between the two phases. We formulate the VN em- bedding problem as a mixed integer program through substrate network augmentation. We then relax the integer constraints to obtain a linear program, and devise two VN embedding algo- rithms D-ViNE and R-ViNE using deterministic and randomized rounding techniques, respectively. Simulation experiments show that the proposed algorithms increase the acceptance ratio and the revenue while decreasing the cost incurred by the substrate network in the long run. This paper attends to the problem of embedding flexibly specified virtual networks connecting cloud resources (e.g., storage or computation) on a given substrate (e.g., a data center, an ISP backbone, a router site, or a virtual provider network). We study a scenario where a substrate provider (or a potential intermediate broker or reseller) wants to optimize the embedding of these so-called by migrating them to more suitable locations. For instance, such re-embeddings can be useful if the were requested at short notice and initially placed heuristically. Subsequent optimizations can, e.g., reduce the peak resource loads in the network by spreading across the infrastructure or save energy by moving together and switching off unused components. We present the generic mathematical programming algorithm used in our prototype to compute optimal embeddings. For example, this algorithm supports different objective functions (such as load minimization or energy conservation), arbitrary resource combinations and the mapping of multiple virtual nodes of a to a single substrate node, cost-aware migrations, and it can deal with all link types that arise in practice (e.g., full-duplex or even wireless or wired broadcast links with multiple endpoints). Of course, such rigorous optimizations are time consuming, and we report on the time complexities obtained from our experiments with our network virtualization prototype architecture. It turns out that optimizing over moderate sized infrastructures is feasible, even for scenarios with high flexibility and without tuning the solver software to speed up computations further.