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virtualized network functions resource allocation in network functions virtualization using mathematical programming

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COMPUTER COMMUNICATIONS 2024年 228卷

作者： Moradi, Mahsa Ahmadi, Mahmood PourKarimi, Latif Razi Univ Comp Engn & Informat Technol Dept Kermanshah Iran Razi Univ Dept Math Kermanshah Iran

network functions Virtualization (NFV) revolutionizes network services by eliminating the need for dedicated hardware. This virtualization enables flexible and efficient deployment of various network functions like proxies, firewalls, and load balancers. Providing the service requested by the user in the network is done by a sequence of virtual network functions, which are known as service functions chain. One of the main challenges in the development of network functions virtualization architecture is the allocation of resources to the requested network services in network infrastructures, this challenge is called network function virtualization resource allocation problem. Therefore, this paper addresses the resource allocation problem in network functions Virtualization (NFV) architectures using mathematical programming techniques. A multi-objective mixed-integer linear programming (MILP) model is proposed to optimize resource allocation for virtual network functions (VNFs). The model incorporates constraints related to node and link resource capacities, as well as delay requirements. The objective functions focus on maximizing network throughput, minimizing node resource costs (CPU cores and memory), reducing capital and operational expenses, and ensuring efficient execution time. These constraints and objective functions are formally defined by mathematical functions. The proposed mathematical model is implemented and solved using the Cplex solver. To evaluate the effectiveness of the proposed mathematical model, various network topologies were evaluated under different parameters. These parameters included the length of Service Function Chains (SFCs), the number and length of flows, node resource capacities, the number of nodes and VNFs. The experimental results demonstrated the model's ability to efficiently allocate resources to VNFs across these different scenarios.

关键词： network functions virtualization architecture virtualized network functions Resource allocation Mathematical programming Mixed integer linear programming

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On the Scaling of virtualized network functions

On the Scaling of Virtualized Network Functions

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IFIP/IEEE Symposium on Integrated network and Service Management (IM)

作者： Rankothge, Windhya Ramalhinho, Helena Lobo, Jorge Sri Lanka Inst Informat Technol Malabe Sri Lanka Univ Pompeu Fabra Barcelona Spain ICREA Barcelona Spain Univ Pompeu Fabra Barcelona Spain

ISBN: (纸本)9783903176157

Offering virtualized network functions (VNFs) as a service requires automation of cloud resource management to allocate cloud resources for the VNFs dynamically. Most of the existing solutions focus only on the initial resource allocation. However, the allocation of resources must adapt to dynamic traffic demands and support fast scaling mechanisms. There are three basic scaling models: vertical where re-scaling is achieved by changing the resources assigned to the VNF in the host server, horizontal where VNFs are replicated or removed to do rescaling, and migration where VNFs are moved to servers with more resources. In this paper, we present an Iterated Local Search (ILS) based framework for automation of resource reallocation that supports the three scaling models. We, then, use the framework to run experiments and compare the different scaling approaches, specifically how the optimization is affected by the scaling approach and the optimization objectives.

关键词： virtualized network functions Cloud Resources Management Iterated Local Search

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ElasticSFC: Auto-scaling techniques for elastic service function chaining in network functions virtualization-based clouds

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JOURNAL OF SYSTEMS AND SOFTWARE 2019年 152卷 108-119页

作者： Toosi, Adel Nadjaran Son, Jungmin Chi, Qinghua Buyya, Rajkumar Monash Univ Fac Informat Technol Clayton Vic Australia Shanghai Huawei Technol Co Ltd Wireless Network Res Dept Shanghai Peoples R China Univ Melbourne Cloud Comp & Distributed Syst CLOUDS Lab Sch Comp & Informat Syst Melbourne Vic Australia

It is anticipated that future networks support network functions, such as firewalls, load balancers and intrusion prevention systems in a fully automated, flexible, and efficient manner. In cloud computing environments, network functions virtualization (NFV) aims to reduce cost and simplify operations of such network services through the virtualization technologies. To enforce network policies in NFV-based cloud environments, network services are composed of virtualized network functions (VNFs) that are chained together as service function chains (SFCs). All network traffic matching a policy must traverse network functions in the chain in a sequence to comply with it. While SFC has drawn considerable attention, relatively little has been given to dynamic auto-scaling of VNF resources in the service chain. Moreover, most of the existing approaches focus only on allocating computing and network resources to VNFs without considering the quality of service requirements of the service chain such as end-to-end latency. Therefore, in this paper, we define a unified framework for building elastic service chains. We propose a dynamic auto-scaling algorithm called ElasticSFC to minimize the cost while meeting the end-to-end latency of the service chain. The experimental results show that our proposed algorithm can reduce the cost of SFC deployment and SLA violation significantly. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Service function chaining network functions virtualization virtualized network functions Software defined networking Auto-scaling Cloud computing

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Approach to Virtualization of Evolved Packet Core network functions 13

Approach to Virtualization of Evolved Packet Core Network Fu...

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13th International Conference on Experience of Designing and Application of CAD Systems in Microelectronics (CADSM)

作者： Skulysh, Mariia Klimovych, Oleg Natl Tech Univ Ukraine Kyiv Polytech Inst Inst Telecommun Syst Kiev Ukraine

ISBN: (纸本)9786176077169

In this paper the main aspects of usage network functions Virtualization (NFV) in the domain of Evolved Packet Core (EPC) virtualization are given. Modern virtualization technologies in combination with existing tools for storage and computing, ensure virtualization and abstraction for the entire set of critical resources. The general aim of NFV is to deliver functions, networks and infrastructure as services rather than as features of vertically integrated systems. Virtualization of EPC components using NFV approach can provide capacity support for mobile broadband services with high level of performance. For operators, the return on investment associated with migrating network services to the cloud comes in the form of a high degree of automation in network operation.

关键词： network functions Virtualization Evolved Packet Core virtualization virtualized network functions

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Knowledge defined networks on the edge for service function chaining and reactive traffic steering

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CLUSTER COMPUTING-THE JOURNAL OF networkS SOFTWARE TOOLS AND APPLICATIONS 2023年第1期26卷 613-634页

作者： Rafiq, Adeel Rehman, Saad Young, Rupert Song, Wang-Cheol Khan, Muhammad Attique Kadry, Seifedine Srivastava, Gautam HITEC Univ Taxila Dept Comp Engn Taxila Pakistan Univ Sussex Sch Engn & Informat Dept Engn & Design Brighton E Sussex England Jeju Natl Univ Dept Comp Engn Jeju South Korea HITEC Univ Taxila Dept Comp Sci Taxila Pakistan Noroff Univ Coll Fac Appl Comp & Technol N-4608 Kristiansand Norway Brandon Univ Dept Math & Comp Sci Brandon MB R7A 6A9 Canada China Med Univ Res Ctr Interneural Comp Taichung 40402 Taiwan

Emerging technologies such as network function virtualization and software-defined networking (SDN) have made a phenomenal breakthrough in network management by introducing softwarization. The provision of assets to each virtualized network functions autonomously as well as efficiently and searching for an optimal pattern for traffic routing challenges are still under consideration. Unfortunately, the traditional methods for estimating the desired performance indicators are insufficient for a self-driven SDN. In the last decade, a combination of machine learning and cognitive techniques construct a knowledge plane (KP) for the Internet which introduces numerous benefits to networking, like automation and recommendation. Furthermore, the inclusion of KP to the conventional three planes SDN architectures recently has added another knowledge defined networking (KDN) architecture to drive an SDN autonomously. In this article, a self-driving system has been proposed based on KDN to achieve the selection of an optimal path for the deployment of service function chaining (SFC) and reactive traffic routing among the edge clouds. Considering the limited resource of edge clouds, the proposed system also maintains a balance among edge cloud resources while orchestrating SFC resources. The graph neural network has been also applied in the proposed system to recognize the composite relationship concerning topology, traffic features, and routing patterns for accurate estimation of key performance indicators. The proposed system improves resource utilization efficiency for SFC deployment by 20%, maximum network throughput by 5%, and CPU load by 13%.

关键词： Edge computing Cloud computing networks Software-defined networking virtualized network functions Machine learning

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Optimization of Virtualization Cost, Processing Power and network Load of 5G Software-Defined Data Centers

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2020年第3期17卷 1542-1553页

作者： Salhab, Nazih Rahim, Rana Langar, Rami Univ Gustave Eiffel CNRS UMR 8049 LIGM F-77420 Champs Sur Marne France Lebanese Univ Fac Sci LTRM Tripoli 1300 Lebanon

Virtualization is getting unprecedented attention from Mobile network Operators (MNOs) as it provides agility in deployment, especially when coupled with the Cloud that offers inherent elasticity and load-balancing of resources. MNOs have to ensure operational excellence by meeting several objectives. In this context, we propose in this paper, a framework for optimizing the mapping of next Generation Node-Bs (gNBs) to Software-Defined 5G Core (5GC) delay tolerant network functions (NFs). These NFs are considered to be deployed as a Virtual Machine (VM) pool, or containers, in order to minimize cloud computing cost, processing power and at the same time maximize network load. First, we formulate this problem as an integer linear program, while taking into account multiple constraints including Virtual Central Processing Unit (vCPU) capacity, central processing load limits and integrality of mapping relations between gNBs and 5GC NFs. Then, we propose an algorithm to solve large problem instances based on Branch, Cut and Price (BCP) combining all of "Branch and Price", "Branch and Cut" and "Branch and Bound" frameworks. We present several schemes reflecting different optimization goals that the MNO can foster: virtualization cost, power minimization, network load or all. Simulation results demonstrate the good performance of our proposed algorithm to solve the gNBs-VM pool mapping for all evaluated schemes, while also emphasizing the advantages of a particular one (EWoS-333 for Equal Weight optimization Scheme) that can decrease virtualization cost by almost one order of magnitude compared to a static selection scheme, while considering the other two objectives.

关键词： Cloud computing Optimization 5G mobile communication Data centers Minimization Virtualization Heuristic algorithms Multi-objective optimization branch cut and price (BCP) 5G mobile network operator (MNO) virtualized network functions

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A Wrapper Feature Selection Based Hybrid Deep Learning Model for DDoS Detection in a network with NFV Behaviors

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WIRELESS PERSONAL COMMUNICATIONS 2023年第1期133卷 481-506页

作者： Tikhe, Gajanan Nanaji Patheja, Pushpinder Singh VIT Bhopal Univ SCSE Bhopal Madhya Pradesh India

network function virtualization (NFV) is a rapidly growing technology that permits network operators to issue their virtualized network functions (VNFs) with cheaper commodity servers. There are various VNFs, namely firewalls, switches, and virtual routers. However, detecting denial of service (DDoS) attacked VNFs is challenging as VNF behaviors are complicated and dynamic due to network traffic in the cloud. Therefore, the proposed work implemented an intrusion detection system (IDS) to detect DDoS attacks in the network. The proposed IDS is named a wrapper feature selection-based hybrid deep learning model (WF-HDL). The DDoS detection model undergoes three stages: pre-processing, feature selection, and detection. The pre-processing is achieved by the z-score normalization technique, followed by a wrapper-based feature selection achieved using the Pelican optimization algorithm (POA). Finally, the DDoS attacks are detected using deep auto-encoder-convolutional gated recurrent unit (DAE-CGRU). The proposed model detected the network's normal and attacked VNF behaviors more accurately. It can train different kinds of VNF behaviour models. In the proposed work, two VNF models, a virtual firewall and a virtual router are trained using a CIC-DDoS2019 dataset. The proposed attack detection model achieves high accuracy at 99.69%, precision at 99.03%, recall at 99.07%, f1-score at 99.05%, and receiver operating characteristic curve (ROC curve) at 99.85%.

关键词： network function virtualization Wrapper feature selection Hybrid deep learning virtualized network functions Denial of service

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Efficient NFV-Enabled Multicasting in SDNs

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IEEE TRANSACTIONS ON COMMUNICATIONS 2019年第3期67卷 2052-2070页

作者： Xu, Zichuan Liang, Weifa Huang, Meitian Jia, Mike Guo, Song Galis, Alex Dalian Univ Technol Sch Software Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116621 Peoples R China Australian Natl Univ Res Sch Comp Sci Canberra ACT 2601 Australia Hong Kong Polytech Univ Shenzhen Res Inst Hong Kong Peoples R China Hong Kong Polytech Univ Dept Comp Hong Kong Peoples R China UCL Dept Elect & Elect Engn London WC1E 7JE England

Multicasting is a fundamental functionality of many network applications, including online conferencing, event monitoring, video streaming, and so on. To ensure reliable, secure, and scalable multicasting, a service chain that consists of network functions (e.g., firewalls, intrusion detection systems, and transcoders) usually is associated with each multicast request. We refer to such a multicast request with service chain requirement as an network function virtualization (NFV)-enabled multicast request. In this paper, we study NFV-enabled multicasting in a software-defined network (SDN) with an aim to maximize network throughput while minimizing the implementation cost of admitted NFV-enabled multicast requests, subject to network resource capacity, where the implementation cost of a request consists of its computing resource consumption cost in servers and its network bandwidth consumption cost when routing and processing its data packets in the network. To this end, we first formulate two NFV-enabled multicasting problems with and without resource capacity constraints and one online NFV-enabled multicasting problem. We then devise two approximation algorithms with an approximation ratio of 2M for the NFV-enabled multicasting problems with and without resource capacity constraints, if the number of servers for implementing the service chain of each request is no greater than a constant M (>= 1). We also study dynamic admissions of NFV-enabled multicast requests without the knowledge of future request arrivals with the objective to maximize the network throughput, for which we propose an efficient heuristic, and for the special case of dynamic request admissions, we devise an online algorithm with a competitive ratio of O(log n) for it when M = 1, where n is the number of nodes in the network. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising

关键词： network function virtualization software-defined networks multicasting NFV-enabled multicasting service chains virtualized network functions routing approximation online algorithms

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Resilient VNF Placement for Service Chain Embedding in Diversified 5G network Slices

Resilient VNF Placement for Service Chain Embedding in Diver...

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IEEE Global Communications Conference (IEEE GLOBECOM)

作者： Mohan, Purnima Murali Gurusamy, Mohan Natl Univ Singapore Dept Elect & Comp Engn Singapore Singapore

ISBN: (纸本)9781728109626

A 5G network slice is comprised of several service chains (SCs) - a chain of virtualized network functions (VNFs) each performing a function (e.g., firewall) to serve diverse traffic requirements. These VNFs are hosted on servers/physicalmachines in one or more data-centers. In this context, a fault/attack on a 5G network could be as fine-grained as a VNF failure or as coarse-grained as the failure of a hosting physical-machine (PM). The latter may lead to multiple VNF failures that may affect several SCs in one or more network slices. To enable resilience towards such failure/attacks, one approach is to protect all the SCs by replicating the VNFs on different PMs. However, such a protection approach will significantly increase the computational and operational costs opposing the 5G network objective. In this paper, we propose an approach for resilient network slice embedding such that the VNFs of a service chain are instantiated on appropriate PMs to minimize the number of affected SCs upon a PM failure. We develop an optimization programming formulation that minimizes the maximum of the affected number of weighted service chains while satisfying the VNF placement and routing constraints in the co-located 5G network slices along with resource (bandwidth, computing) and slice-specific requirements. We evaluate the proposed resilient mapping approach through numerical analysis and show that it achieves a resilience factor of up to 0.88 while requiring 78% less number of VNF replicas on an average, when compared to the protection-based approach.

关键词： 5G network slicing virtualized network functions Service chain embedding Resilience

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Energy-efficient Virtual network Function Placement in Telecom networks

Energy-efficient Virtual Network Function Placement in Telec...

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IEEE International Conference on Communications (ICC) / Workshop on Integrating UAVs into 5G

作者： Xu, Zhichao Zhang, Xiaoning Yu, Shui Zhang, Ji Univ Elect Sci & Technol China Sch Commun & Informat Engn Chengdu Peoples R China Deakin Univ Sch Informat Technol Geelong Vic Australia

ISBN: (纸本)9781538631805

network Function Virtualization (NFV) is an emerging network architecture, which decouples the software implementation of network functions from the underlying hardware. Telecom operators widely place diverse types of Virtual network functions (VNFs) on specified software middlebox. Traffic needs to go through a set of ordered VNFs which forms a Service Function Chain (SFC). However, how to efficiently place VNFs at various network locations while minimizing energy consumption is still an open problem. To this end, we study joint optimization of VNF placement and traffic routing for energy efficiency in telecom networks. We first present the energy model in NFV-enabled telecom networks, and then formulate the studied problem as an Integer Linear Programming (ILP) model. Since the problem is NP-hard, we design a polynomial algorithm using the Markov approximation technique to find the near-optimal result. Extensive simulation results show that our algorithm saves up to 14.84% energy consumption in telecom networks compared with previous VNF placement algorithms.

关键词： virtualized network functions Service Function Chain Energy Efficiency Markov Approximation

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