24,368 research outputs found
Optimal Orchestration of Virtual Network Functions
-The emergence of Network Functions Virtualization (NFV) is bringing a set of
novel algorithmic challenges in the operation of communication networks. NFV
introduces volatility in the management of network functions, which can be
dynamically orchestrated, i.e., placed, resized, etc. Virtual Network Functions
(VNFs) can belong to VNF chains, where nodes in a chain can serve multiple
demands coming from the network edges. In this paper, we formally define the
VNF placement and routing (VNF-PR) problem, proposing a versatile linear
programming formulation that is able to accommodate specific features and
constraints of NFV infrastructures, and that is substantially different from
existing virtual network embedding formulations in the state of the art. We
also design a math-heuristic able to scale with multiple objectives and large
instances. By extensive simulations, we draw conclusions on the trade-off
achievable between classical traffic engineering (TE) and NFV infrastructure
efficiency goals, evaluating both Internet access and Virtual Private Network
(VPN) demands. We do also quantitatively compare the performance of our VNF-PR
heuristic with the classical Virtual Network Embedding (VNE) approach proposed
for NFV orchestration, showing the computational differences, and how our
approach can provide a more stable and closer-to-optimum solution
Specifying and Placing Chains of Virtual Network Functions
Network appliances perform different functions on network flows and
constitute an important part of an operator's network. Normally, a set of
chained network functions process network flows. Following the trend of
virtualization of networks, virtualization of the network functions has also
become a topic of interest. We define a model for formalizing the chaining of
network functions using a context-free language. We process deployment requests
and construct virtual network function graphs that can be mapped to the
network. We describe the mapping as a Mixed Integer Quadratically Constrained
Program (MIQCP) for finding the placement of the network functions and chaining
them together considering the limited network resources and requirements of the
functions. We have performed a Pareto set analysis to investigate the possible
trade-offs between different optimization objectives
Getting the Most Out of Your VNFs: Flexible Assignment of Service Priorities in 5G
Through their computational and forwarding capabilities, 5G networks can
support multiple vertical services. Such services may include several common
virtual (network) functions (VNFs), which could be shared to increase resource
efficiency. In this paper, we focus on the seldom studied VNF-sharing problem,
and decide (i) whether sharing a VNF instance is possible/beneficial or not,
(ii) how to scale virtual machines hosting the VNFs to share, and (iii) the
priorities of the different services sharing the same VNF. These decisions are
made with the aim to minimize the mobile operator's costs while meeting the
verticals' performance requirements. Importantly, we show that the
aforementioned priorities should not be determined a priori on a per-service
basis, rather they should change across VNFs since such additional flexibility
allows for more efficient solutions. We then present an effective methodology
called FlexShare, enabling near-optimal VNF-sharing decisions in polynomial
time. Our performance evaluation, using real-world VNF graphs, confirms the
effectiveness of our approach, which consistently outperforms baseline
solutions using per-service priorities
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