288 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
Semantic validation of affinity constrained service function chain requests
Network Function Virtualization (NFV) has been proposed as a paradigm to increase the cost-efficiency, flexibility and innovation in network service provisioning. By leveraging IT virtualization techniques in combination with programmable networks, NFV is able to decouple network functionality from the physical devices on which they
are deployed. This opens up new business opportunities for both Infrastructure Providers (InPs) as well as Service Providers (SPs), where the SP can request to deploy a chain of Virtual Network Functions (VNFs) on top of which its service can run. However, current NFV approaches lack the possibility for SPs to define location requirements and constraints on the mapping of virtual functions and paths onto physical hosts and links. Nevertheless, many scenarios
can be envisioned in which the SP would like to attach placement constraints for efficiency, resilience, legislative, privacy and economic reasons. Therefore, we propose a set of affinity and anti-affinity constraints, which can be used by SPs to define such placement restrictions. This newfound ability to add constraints to Service Function Chain (SFC) requests also introduces an additional risk that SFCs with conflicting constraints are requested or automatically
generated. Therefore, a framework is proposed that allows the InP to check the validity of a set of constraints and provide feedback to the SP. To achieve this, the SFC request and relevant information on the physical topology are modeled as an ontology of which the consistency can be checked using a semantic reasoner. Enabling semantic
validation of SFC requests, eliminates inconsistent SFCs requests from being transferred to the embedding algorithm.Peer Reviewe
Algorithms for advance bandwidth reservation in media production networks
Media production generally requires many geographically distributed actors (e.g., production houses, broadcasters, advertisers) to exchange huge amounts of raw video and audio data. Traditional distribution techniques, such as dedicated point-to-point optical links, are highly inefficient in terms of installation time and cost. To improve efficiency, shared media production networks that connect all involved actors over a large geographical area, are currently being deployed. The traffic in such networks is often predictable, as the timing and bandwidth requirements of data transfers are generally known hours or even days in advance. As such, the use of advance bandwidth reservation (AR) can greatly increase resource utilization and cost efficiency. In this paper, we propose an Integer Linear Programming formulation of the bandwidth scheduling problem, which takes into account the specific characteristics of media production networks, is presented. Two novel optimization algorithms based on this model are thoroughly evaluated and compared by means of in-depth simulation results
Joint Energy Efficient and QoS-aware Path Allocation and VNF Placement for Service Function Chaining
Service Function Chaining (SFC) allows the forwarding of a traffic flow along
a chain of Virtual Network Functions (VNFs, e.g., IDS, firewall, and NAT).
Software Defined Networking (SDN) solutions can be used to support SFC reducing
the management complexity and the operational costs. One of the most critical
issues for the service and network providers is the reduction of energy
consumption, which should be achieved without impact to the quality of
services. In this paper, we propose a novel resource (re)allocation
architecture which enables energy-aware SFC for SDN-based networks. To this
end, we model the problems of VNF placement, allocation of VNFs to flows, and
flow routing as optimization problems. Thereafter, heuristic algorithms are
proposed for the different optimization problems, in order find near-optimal
solutions in acceptable times. The performance of the proposed algorithms are
numerically evaluated over a real-world topology and various network traffic
patterns. The results confirm that the proposed heuristic algorithms provide
near optimal solutions while their execution time is applicable for real-life
networks.Comment: Extended version of submitted paper - v7 - July 201
Probabilistic QoS-aware Placement of VNF chains at the Edge
Deploying IoT-enabled Virtual Network Function (VNF) chains to Cloud-Edge
infrastructures requires determining a placement for each VNF that satisfies
all set deployment requirements as well as a software-defined routing of
traffic flows between consecutive functions that meets all set communication
requirements. In this article, we present a declarative solution, EdgeUsher, to
the problem of how to best place VNF chains to Cloud-Edge infrastructures.
EdgeUsher can determine all eligible placements for a set of VNF chains to a
Cloud-Edge infrastructure so to satisfy all of their hardware, IoT, security,
bandwidth, and latency requirements. It exploits probability distributions to
model the dynamic variations in the available Cloud-Edge infrastructure, and to
assess output eligible placements against those variations
Formal assurance of security policies in automated network orchestration (SDN/NFV)
1noL'abstract è presente nell'allegato / the abstract is in the attachmentopen677. INGEGNERIA INFORMATInoopenYusupov, Jalolliddi
Security-aware Resource Allocation for Space-Air-Ground Integrated Network using Deep Reinforcement Learning
A Space-Air-Ground Integrated Network (SAGIN) has been proposed to extend communication network service coverage to consumer-oriented and industrial sectors where communication network coverage is either limited or unavailable. To effectively use the space, air, and ground hardware resources, Network Function Virtualization (NFV) is introduced into SAGIN. NFV enables the deployment and management of services that are represented as Virtual Networks (VN) composed of Virtual Network Functions (VNF) onto the SAGIN hardware through hardware virtualization. This enables SAGIN to support services with distinct demands from both consumer-oriented and industrial sectors.
However, by introducing NFV into SAGIN, new security vulnerabilities arise. For instance, if a malicious entity gains access to the virtualized hardware, all services utilizing the hardware are exposed to attack.
When deploying a VN onto the SAGIN hardware, also known as the Substrate Network (SN), it must be decided which SN Node (SNN) should host each VN Node (VNN) and which SN Links (SNL) should host each VN Link (VNL), also known as the Virtual Network Embedding (VNE) problem. This thesis proposes a solution to VNE in SAGIN using Deep Reinforcement Learning (DRL) while accounting for the security concerns related to NFV. To our knowledge, this has yet to be explored by other works.
We compare our solution with the well-known Global Resource Capacity (GRC) solution strategy using the acceptance rate, revenue, cost, and revenue-to-cost metrics. Our DRL-based solution strategy shows competitive performance in all metrics
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