Deployment Of Virtual Networks Research Articles

On Optimal Orchestration of Virtualized Cellular Networks With Statistical Multiplexing

Wireless network virtualization is emerging as a promising technology for cellular networks. A key advantage of introducing virtualization in cellular networks is that wireless services can be decoupled from network resources (e.g., infrastructure and spectrum) so that multiple virtual networks can be built using a shared pool of network resources. This paper develops an optimization framework for orchestrating virtualized cellular networks while enabling and exploiting statistical multiplexing. Our proposed framework has two phases: virtual network deployment (static) and statistical multiplexing (adaptive). In the virtual network deployment phase, network resources are aggregated, sliced, and allocated to the virtual networks considering the presence of uncertainty in user equipment (UE) locations and channel conditions, without knowing which realization of UE locations and channel conditions will occur. Once the virtual networks are deployed, each of the aggregated base stations (BSs) performs statistical multiplexing, i.e., allocates excess resources from the over-satisfied slices to the under-satisfied slices, according to the realized channel conditions of associated UEs. Our numerical results demonstrate that the proposed framework outperforms existing virtualization frameworks in terms of probabilistically satisfying virtual networks’ rate and coverage demands while minimizing resource over-provisioning, in the presence of uncertainty in UE locations and channel conditions.

Dynamic Virtual Network Reconfiguration Method for Hybrid Multiple Failures Based on Weighted Relative Entropy.

Network virtualization can offer more flexibility and better manageability for next generation Internet. With the increasing deployments of virtual networks in military and commercial networks, a major challenge is to ensure virtual network survivability against hybrid multiple failures. In this paper, we study the problem of recovering virtual networks affected by hybrid multiple failures in substrate networks and provide an integer linear programming formulation to solve it. We propose a heuristic algorithm to tackle the complexity of the integer linear programming formulation, which includes a faulty virtual network reconfiguration ranking method based on weighted relative entropy, a hybrid multiple failures ranking algorithm, and a virtual node migration method based on weighted relative entropy. In the faulty virtual network reconfiguration ranking method based on weighted relative entropy and virtual node migration method based on weighted relative entropy, multiple ranking indicators are combined in a suitable way based on weighted relative entropy. In the hybrid multiple failures ranking algorithm, the virtual node and its connective virtual links are re-embedded, firstly. Evaluation results show that our heuristic method not only has the best acceptance ratio and normal operation ratio, but also achieves the highest long-term average revenue to cost ratio compared with other virtual network reconfiguration methods.

Generalized Recovery From Node Failure in Virtual Network Embedding

Network virtualization has evolved as a key enabling technology for offering the next generation network services. Recently, it is being rolled out in data center networks as a means to provide bandwidth guarantees to cloud applications. With increasing deployments of virtual networks (VNs) in commercial-grade networks with commodity hardware, VNs need to tackle failures in the underlying substrate network. In this paper, we study the problem of recovering a batch of VNs affected by a substrate node failure. The combinatorial possibilities of alternate embeddings of the failed virtual nodes and links of the VNs make the task of finding the most efficient recovery both non-trivial and intractable. Furthermore, any recovery approach ideally should not cause any service disruption for the unaffected parts of the VNs. We take into account these issues to design a generalized recovery approach that can achieve customized objectives such as fair treatment on the failed VNs, partial treatment based on priority, and so on. We provide integer linear programming (ILP) formulations for two variants of our recovery scheme, namely, fair recovery model and priority-based recovery model. We also propose a fast and scalable heuristic algorithm to tackle the computational complexity of the ILP solution. Evaluation results demonstrate that our heuristic performs close to the optimal solution and outperforms the state-of-the-art algorithm.

Two-criteria Pareto frontier for virtual network allocation on Edge-as-a-Service networks

Nowadays, the Internet is part of our lives, being an essential way of communication. However, it suffers from limitations that prevent the Internet to guarantee Quality of Service (QoS) for the services to the clients. Recently, the scientific community presented the Edge as a Service (EaaS) paradigm as a possible approach to improve the Internet access service. EaaS is based on the deployment of Virtual Networks (VNs) over Software Defined Networks to ease the management of Internet Service Providers (ISPs) through the supporting of Service Level Agreements (SLAs) and the allocation schemes that consider the network resources. Furthermore, the ISPs aim to maximize their profit by establishing as many SLAs as possible and decrease the energy consumption to deliver their services, where reliability and available bandwidth are key requirements. Thus, the EaaS needs an allocation algorithm to allow the deployment of VNs considering all these points. Within this context, this paper presents the PAreto based on Bandwidth and ENergy (PABEN) algorithm to deploy the VNs based on a Pareto frontier (using bandwidth availability and energy efficiency information), as well as considering a minimum reliability. The results suggest that the proposed algorithm can deploy reliable VNs, while improving bandwidth utilization and energy consumption.

Optimal construction of virtual networks for Cloud-based MapReduce workflows

Cloud-based big data platforms are being widely adopted in industry, due to their advantages of facilitating the implementation of big data processing and enabling elastic service frameworks. With the widespread adoption of cloud-based MapReduce frameworks, a series of solutions have been proposed to improve the performance of big data services over cloud. The majority of the existing studies concentrate on optimizing the task scheduling or resource provisioning mechanisms, to improve the data processing rate or data transmission rate of the platform separately, without an overall consideration of both the performance factors. Moreover, these studies seldom consider the impact of virtual network topologies on the performance of the cloud-based MapReduce workflows. The purpose of this work is to optimize the topologies of virtual networks used in cloud-based MapReduce frameworks. We formulate both the data transmission and data processing overhead of a specific cloud-based big data application, describe the optimal deployment of virtual networks as an optimization problem and then design algorithms to solve this problem. Experimental results show that our topology optimization mechanism improves the overall performance of cloud-based big data applications effectively.

Wireless Cloud Networks for the Factory of Things: Connectivity Modeling and Layout Design

Large-scale adoption of dense cloud-based wireless network technologies in industrial plants is mandatorily paired with the development of methods and tools for connectivity prediction and deployment validation. Layout design procedures must be able to certify the quality (or reliability) of network information flow in industrial scenarios characterized by harsh propagation environments. In addition, these procedures must account for possibly coexisting heterogeneous radio access technologies as part of the Internet of Things (IoT) paradigm, easily allow post-layout validation steps, and be integrated by industry-standard CAD-based planning systems. The goal of the paper is to set the fundamentals for comprehensive industry-standard methods and procedures supporting plant designer during wireless coverage prediction, virtual network deployment, and post-layout verification. The proposed methods carry out the prediction of radio signal coverage considering typical industrial environments characterized by highly dense building blockage. They also provide a design framework to properly deploy the wireless infrastructure in interference-limited radio access scenarios. In addition, the model can be effectively used to certify the quality of machine-type communication by considering also imperfect descriptions of the network layout. The design procedures are corroborated by experimental measurements in an oil refinery site [modeled by three-dimensional (3-D) CAD] using industry-standard ISA IEC 62734 devices operating at 2.4 GHz. A graph-theoretic approach to node deployment is discussed by focusing on practical case studies, and also by looking at fundamental connectivity properties for random deployments.

Position Paper: Secure Virtual Network Embedding

Network virtualization has been recognized as an important technique to overcome the perceived ossification of the current Internet. Several variations of network virtualization have already been discussed in the literature. These approaches use virtualization to partition and/or combine physical network resources into virtual network resources. An actual deployment of virtual networks then requires the network operator to perform a mapping of virtual resources onto physical resources. The question of how this mapping can be performed in an optimal way is commonly known as the Virtual Network Embedding (VNE) problem. Several algorithms to solve this problem have been proposed already. These algorithms, however, focus on optimizing the use of resources with regard to performance. Security constraints to the VNE problem have not been investigated in depth, so far.