Juan Felipe Botero

Energy Efficient Virtual Network Embedding

Waste of energy due to over-provisioning and over-dimensioning of network infrastructures has recently stimulated the interest on energy consumption reduction by Internet Service Providers (ISPs). By means of resource consolidation, network virtualization based architectures will enable energy saving. In this letter, we extend the well-known virtual network embedding problem (VNE) to energy awareness and propose a mixed integer program (MIP) which provides optimal energy efficient embeddings. Simulation results show the energy gains of the proposed MIP over the existing cost-based VNE approach.

Resource Allocation in NFV: A Comprehensive Survey

Network functions virtualization (NFV) is a new network architecture framework where network function that traditionally used dedicated hardware (middleboxes or network appliances) are now implemented in software that runs on top of general purpose hardware such as high volume server. NFV emerges as an initiative from the industry (network operators, carriers, and manufacturers) in order to increase the deployment flexibility and integration of new network services with increased agility within operators networks and to obtain significant reductions in operating expenditures and capital expenditures. NFV promotes virtualizing network functions such as transcoders, firewalls, and load balancers, among others, which were carried out by specialized hardware devices and migrating them to software-based appliances. One of the main challenges for the deployment of NFV is the resource allocation of demanded network services in NFV-based network infrastructures. This challenge has been called the NFV resource allocation (NFV-RA) problem. This paper presents a comprehensive state of the art of NFV-RA by introducing a novel classification of the main approaches that pose solutions to solve it. This paper also presents the research challenges that are still subject of future investigation in the NFV-RA realm.

Optimal mapping of virtual networks with hidden hops

Network virtualization has emerged as a solution for the Internet inability to address the required challenges caused by the lack of coordination among Internet service providers for the deployment of new services. The allocation of resources is one of the main problems in network virtualization, mainly in the mapping of virtual nodes and links to specific substrate nodes and paths, also known as the virtual network embedding problem. This paper proposes an algorithm based on optimization theory, to map the virtual links and nodes requiring a specific demand, looking for the maximization of the spare bandwidth and spare CPU in the substrate network, taking into account the CPU demanded by the hidden hops when a virtual link is mapped. The components of the virtual networks (nodes and links) that do not ask for an specific demand are then allocated following a fairness criteria.

Greener networking in a network virtualization environment

Energy consumption of network operators can be minimized by the dynamic and smart relocation of networking resources. In this paper, we propose to take advantage of network virtualization to enable a smart energy aware network provisioning. The virtualization of networking resources leads to the problem of mapping virtual demands to physical resources, known as Virtual Network Embedding (VNE). Our proposal modifies and improves exact existing energy aware VNE proposals where the objective is to switch off as many network nodes and interfaces as possible by allocating the virtual demands to a consolidated subset of active physical networking equipment. As exact energy efficient VNE approaches are hard to solve for large network sizes and have an adverse effect in the number of successful embeddings, an heuristic approach to reconfigure the allocation of already embedded virtual networks, minimizing the energy consumption, is also proposed.

ALEVIN - A Framework to Develop, Compare, and Analyze Virtual Network Embedding Algorithms

Network virtualization is recognized as an enabling technology for the Future Internet. Applying virtualization of network resources leads to the problem of mapping virtual resources to physical resources, known as “Virtual Network Embedding” (VNE). Several algorithms attempting to solve this problem have been discussed in the literature, so far. However, comparison of VNE algorithms is hard, as each algorithm focuses on different criteria. To that end, we introduce a framework to compare different algorithms according to a set of metrics, which allow to evaluate the algorithms and compute their results on a given scenario for arbitrary parameters.

Coordinated Allocation of Service Function Chains

Network Functions Virtualization (NFV) is an emerging initiative to overcome increasing operational and capital costs faced by network operators due to the need to physically locate network functions in specific hardware appliances. In NFV, standard IT virtualization evolves to consolidate network functions onto high volume servers, switches and storage that can be located anywhere in the network. Services are built by chaining a set of Virtual Network Functions (VNFs) deployed on commodity hardware. The implementation of NFV leads to the challenge: How several network services (VNF chains) are optimally orchestrated and allocated on the substrate network infrastructure? In this paper, we address this problem and propose CoordVNF, a heuristic method to coordinate the composition of VNF chains and their embedding into the substrate network. CoordVNF aims to minimize bandwidth utilization while computing results within reasonable runtime.

A distributed, parallel, and generic virtual network embedding framework

One of the main challenges of network virtualization is the mapping of virtual network demands to physical network resources, commonly known as the virtual network embedding (VNE) problem. This paper introduces DPVNE, a distributed, parallel and generic VNE framework. DPVNE can be used 1) to run various cost-reducing embedding algorithms 2) in a distributed way. Thereby, computational load for embedding multiple virtual networks is spread across the substrate network reducing workload of individual nodes and 3) enabling the embedding of multiple virtual networks in parallel. DPVNE, in contrast to existing distributed algorithms, 4) achieves lower message overhead and, despite of being distributed, 5) keeps embedding costs comparable to those of centralized approaches.

Distributed and scalable embedding of virtual networks

Network virtualization is widely regarded as a key technology for the Future Internet, enabling the deployment of new network protocols without changing dissimilar hardware devices. This leads to the problem of mapping virtual demands to physical resources, known as Virtual Network Embedding (VNE). Current VNE algorithms do not scale with respect to the substrate network size. Therefore, these algorithms are not applicable in large-scale scenarios where virtual networks have to be embedded in a timely manner.This paper discusses DPVNE, a Distributed and Generic VNE framework: It runs cost-oriented centralized embedding algorithms in a distributed way, spreading workload across the substrate network instead of concentrating it on one single node (as centralized algorithms do). Several state-of-the-art algorithms were evaluated running inside the DPVNE framework. Results show that DPVNE leads to runtime improvements in large-scale scenarios and embedding results are kept comparable.

The bottlenecked virtual network problem in bandwidth allocation for network virtualization

Internet is becoming unable to overcome the challenges required by new services due to the lack of coordination among Internet service providers. This situation, frequently called network ossification, makes increasingly hard the deployment and the testing new network technologies.

Scalable and coordinated allocation of service function chains

Network Functions Virtualization is an emerging initiative where standard IT virtualization evolves to consolidate network functions onto high volume servers, switches and storage that can be located anywhere in the network. In NFV, network services are built by chaining a set of Virtual Network Functions (VNFs) that must be allocated on top of the physical network infrastructure (commodity hardware). This challenge is commonly known as the NFV resource allocation problem, that is divided in two problem stages: 1) service chain composition and 2) service chain embedding. Up to now, existing approaches do not scale with regard to problem size. In this paper, we address this problem and propose CoordVNF, a heuristic method to coordinate the composition of VNF chains and their embedding into the substrate network. Evaluation results show that the heuristic is able to quickly solve the allocation problem even in substrate network topologies with hundreds of nodes.