Relevant bibliographies by topics / Service Function Chain Placement

Academic literature on the topic 'Service Function Chain Placement'

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Published: 11 March 2023

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Journal articles on the topic "Service Function Chain Placement"

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Khoshkholghi, Mohammad Ali, Michel Gokan Khan, Kyoomars Alizadeh Noghani, Javid Taheri, Deval Bhamare, Andreas Kassler, Zhengzhe Xiang, Shuiguang Deng, and Xiaoxian Yang. "Service Function Chain Placement for Joint Cost and Latency Optimization." Mobile Networks and Applications 25, no. 6 (November 21, 2020): 2191–205. http://dx.doi.org/10.1007/s11036-020-01661-w.

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AbstractNetwork Function Virtualization (NFV) is an emerging technology to consolidate network functions onto high volume storages, servers and switches located anywhere in the network. Virtual Network Functions (VNFs) are chained together to provide a specific network service, called Service Function Chains (SFCs). Regarding to Quality of Service (QoS) requirements and network features and states, SFCs are served through performing two tasks: VNF placement and link embedding on the substrate networks. Reducing deployment cost is a desired objective for all service providers in cloud/edge environments to increase their profit form demanded services. However, increasing resource utilization in order to decrease deployment cost may lead to increase the service latency and consequently increase SLA violation and decrease user satisfaction. To this end, we formulate a multi-objective optimization model to joint VNF placement and link embedding in order to reduce deployment cost and service latency with respect to a variety of constraints. We, then solve the optimization problem using two heuristic-based algorithms that perform close to optimum for large scale cloud/edge environments. Since the optimization model involves conflicting objectives, we also investigate pareto optimal solution so that it optimizes multiple objectives as much as possible. The efficiency of proposed algorithms is evaluated using both simulation and emulation. The evaluation results show that the proposed optimization approach succeed in minimizing both cost and latency while the results are as accurate as optimal solution obtained by Gurobi (5%).
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Dang-Quang, Nhat-Minh, and Myungsik Yoo. "Optimized placement of symmetrical service function chain in network function virtualization." Computer Science and Information Systems, no. 00 (2022): 6. http://dx.doi.org/10.2298/csis210920006d.

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Network function virtualization (NFV) is one of the key technology enablers for actualizing 5G networks. With NFV, virtual network functions (VNFs) are linked together as a service function chain (SFC), which provides network functionality for the customer on demand. However, how to efficiently find a suitable placement for VNFs regarding the given objectives is an extremely difficult issue. The existing approaches assume that the SFC has a simple and asymmetrical pattern that is unsuitable to modeling a real system. We address this limitation by studying a VNF placement optimization problem with symmetrical SFCs that can support both symmetric and asymmetric traffic flows. This NP-hard problem is formulated as a mixed-integer linear programming (MILP) model. An iterative greedy-based heuristic is proposed to overcome the complexity of the MILP model. Extensive simulation results show that the proposed heuristic can obtain a near-optimal solution compared to MILP for a small-scale network, and at the same time, is superior to a traditional heuristic for a large-scale network.
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Xu, Yansen, and Ved P. Kafle. "An Availability-Enhanced Service Function Chain Placement Scheme in Network Function Virtualization." Journal of Sensor and Actuator Networks 8, no. 2 (June 14, 2019): 34. http://dx.doi.org/10.3390/jsan8020034.

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A service function chain (SFC) is an ordered virtual network function (VNF) chain for processing traffic flows to deliver end-to-end network services in a virtual networking environment. A challenging problem for an SFC in this context is to determine where to deploy VNFs and how to route traffic between VNFs of an SFC on a substrate network. In this paper, we formulate an SFC placement problem as an integer linear programing (ILP) model, and propose an availability-enhanced VNF placing scheme based on the layered graphs approach. To improve the availability of SFC deployment, our scheme distributes VNFs of an SFC to multiple substrate nodes to avoid a single point of failure. We conduct numerical analysis and computer simulation to validate the feasibility of our SFC scheme. The results show that the proposed scheme outperforms well in different network scenarios in terms of end-to-end delay of the SFC and computation time cost.
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Abdelaal, Marwa A., Gamal A. Ebrahim, and Wagdy R. Anis. "Efficient Placement of Service Function Chains in Cloud Computing Environments." Electronics 10, no. 3 (January 30, 2021): 323. http://dx.doi.org/10.3390/electronics10030323.

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The widespread adoption of network function virtualization (NFV) leads to providing network services through a chain of virtual network functions (VNFs). This architecture is called service function chain (SFC), which can be hosted on top of commodity servers and switches located at the cloud. Meanwhile, software-defined networking (SDN) can be utilized to manage VNFs to handle traffic flows through SFC. One of the most critical issues that needs to be addressed in NFV is VNF placement that optimizes physical link bandwidth consumption. Moreover, deploying SFCs enables service providers to consider different goals, such as minimizing the overall cost and service response time. In this paper, a novel approach for the VNF placement problem for SFCs, called virtual network functions and their replica placement (VNFRP), is introduced. It tries to achieve load balancing over the core links while considering multiple resource constraints. Hence, the VNF placement problem is first formulated as an integer linear programming (ILP) optimization problem, aiming to minimize link bandwidth consumption, energy consumption, and SFC placement cost. Then, a heuristic algorithm is proposed to find a near-optimal solution for this optimization problem. Simulation studies are conducted to evaluate the performance of the proposed approach. The simulation results show that VNFRP can significantly improve load balancing by 80% when the number of replicas is increased. Additionally, VNFRP provides more than a 54% reduction in network energy consumption. Furthermore, it can efficiently reduce the SFC placement cost by more than 67%. Moreover, with the advantages of a fast response time and rapid convergence, VNFRP can be considered as a scalable solution for large networking environments.
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Engelmann, Anna, and Admela Jukan. "A Combinatorial Reliability Analysis of Generic Service Function Chains in Data Center Networks." ACM Transactions on Modeling and Performance Evaluation of Computing Systems 6, no. 3 (September 30, 2021): 1–24. http://dx.doi.org/10.1145/3477046.

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In data center networks, the reliability of Service Function Chain (SFC)—an end-to-end service presented by a chain of virtual network functions (VNFs)—is a complex and specific function of placement, configuration, and application requirements, both in hardware and software. Existing approaches to reliability analysis do not jointly consider multiple features of system components, including, (i) heterogeneity, (ii) disjointness, (iii) sharing, (iv) redundancy, and (v) failure interdependency. To this end, we develop a novel analysis of service reliability of the so-called generic SFC, consisting of n = k + r sub-SFCs, whereby k ≥ 1 and r ≥ 0 are the numbers of arbitrary placed primary and backup (redundant) sub-SFCs, respectively. Our analysis is based on combinatorics and a reduced binomial theorem—resulting in a simple approach, which, however, can be utilized to analyze rather complex SFC configurations. The analysis is practically applicable to various VNF placement strategies in arbitrary data center configurations, and topologies and can be effectively used for evaluation and optimization of reliable SFC placements.
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Wang, Zenan, Jiao Zhang, Tao Huang, and Yunjie Liu. "Service Function Chain Composition, Placement, and Assignment in Data Centers." IEEE Transactions on Network and Service Management 16, no. 4 (December 2019): 1638–50. http://dx.doi.org/10.1109/tnsm.2019.2933872.

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Wang, Yun, Chih-Kai Huang, Shan-Hsiang Shen, and Ge-Ming Chiu. "Adaptive Placement and Routing for Service Function Chains With Service Deadlines." IEEE Transactions on Network and Service Management 18, no. 3 (September 2021): 3021–36. http://dx.doi.org/10.1109/tnsm.2021.3086977.

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Li, Wei, Yuan Jiang, Xiaoliang Zhang, Fangfang Dang, Feng Gao, Haomin Wang, and Qi Fan. "Reliability Assurance Dynamic SSC Placement Using Reinforcement Learning." Information 13, no. 2 (January 21, 2022): 53. http://dx.doi.org/10.3390/info13020053.

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Software-defined networking (SDN) and network function virtualization (NFV) make a network programmable, resulting in a more flexible and agile network. An important and promising application for these two technologies is network security, where they can dynamically chain virtual security functions (VSFs), such as firewalls, intrusion detection systems, and intrusion prevention systems, and thus inspect, monitor, or filter traffic flows in cloud data center networks. In view of the strict delay constraints of security services and the high failure probability of VSFs, we propose the use of a security service chain (SSC) orchestration algorithm that is latency aware with reliability assurance (LARA). This algorithm includes an SSC orchestration module and VSF backup module. We first use a reinforcement learning (RL) based Q-learning algorithm to achieve efficient SSC orchestration and try to reduce the end-to-end delay of services. Then, we measure the importance of the physical nodes carrying the VSF instance and backup VSF according to the node importance of VSF. Extensive simulation results indicate that the LARA algorithm is more effective in reducing delay and ensuring reliability compared with other algorithms.
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Subramanya, Tejas, Davit Harutyunyan, and Roberto Riggio. "Machine learning-driven service function chain placement and scaling in MEC-enabled 5G networks." Computer Networks 166 (January 2020): 106980. http://dx.doi.org/10.1016/j.comnet.2019.106980.

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Bi, Yu, Carlos Colman Meixner, Monchai Bunyakitanon, Xenofon Vasilakos, Reza Nejabati, and Dimitra Simeonidou. "Multi-Objective Deep Reinforcement Learning Assisted Service Function Chains Placement." IEEE Transactions on Network and Service Management 18, no. 4 (December 2021): 4134–50. http://dx.doi.org/10.1109/tnsm.2021.3127685.

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Dissertations / Theses on the topic "Service Function Chain Placement"

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Behravesh, Rasoul <1988&gt. "Life-cycle management and placement of service function chains in MEC-enabled 5G networks." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9732/1/Thesis.pdf.

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Recent advancements in mobile communication technology have led to the fifth generation of mobile cellular networks (5G), driven by the proliferation in data traffic demand, stringent latency requirements, and the desire for a fully connected world. This transformation calls for novel technology solutions such as Multi-access Edge Computing (MEC) and Network Function Virtualization (NFV) to satisfy service requirements while providing dynamic and instant service deployment. MEC and NFV are two principal and complementary enablers for 5G networks whose co-existence can lead to numerous benefits. Despite the numerous advantages MEC offers, physical resources at the edge are extremely scarce and require efficient utilization. In this doctoral dissertation, we first attempt to optimize resource utilization at the network edge for the scenario of live video streaming. We specifically utilize the real-time Radio Access Network (RAN) information available at the MEC servers to develop a machine learning-based prediction solution and anticipate user requests. Consequently, Integer Linear Programming (ILP) models are used to prefetch/cache video contents from a centralized video server. Regarding the advantages of NFV technology for the deployment of NFs, the second problem that this dissertation address is the proper association of the users to the gNBs along with efficient placement of SFCs on the substrate network. Our primary purpose is to find a proper embedding of the SFC in a hierarchical 5G network. The problem is formulated as a Mixed Integer Linear Programming (MILP) model, having the objective to minimize service provisioning cost, link utilization, and the effect of VNF migration on users' perceived quality of experience. After rigorously analyzing the proposed SFC placement and considering mobile networks' dynamicity, our next goal is to develop an ILP-based model that minimizes the resource provisioning cost by dynamically embed and scale SFCs so that provisioning cost is minimized while user requirements are met.
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Subramanya, Tejas. "Autonomic Management and Orchestration Strategies in MEC-Enabled 5G Networks." Doctoral thesis, Università degli studi di Trento, 2021. http://hdl.handle.net/11572/320883.

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5G and beyond mobile network technology promises to deliver unprecedented ultra-low latency and high data rates, paving the way for many novel applications and services. Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) are two technologies expected to play a vital role in achieving ambitious Quality of Service requirements of such applications. While NFV provides flexibility by enabling network functions to be dynamically deployed and inter-connected to realize Service Function Chains (SFC), MEC brings the computing capability to the mobile network's edges, thus reducing latency and alleviating the transport network load. However, adequate mechanisms are needed to meet the dynamically changing network service demands (i.e., in single and multiple domains) and optimally utilize the network resources while ensuring that the end-to-end latency requirement of services is always satisfied. In this dissertation work, we break the problem into three separate stages and present the solutions for each one of them.Firstly, we apply Artificial Intelligence (AI) techniques to drive NFV resource orchestration in MEC-enabled 5G architectures for single and multi-domain scenarios. We propose three deep learning approaches to perform horizontal and vertical Virtual Network Function (VNF) auto-scaling: (i) Multilayer Perceptron (MLP) classification and regression (single-domain), (ii) Centralized Artificial Neural Network (ANN), centralized Long-Short Term Memory (LSTM) and centralized Convolutional Neural Network-LSTM (CNN-LSTM) (single-domain), and (iii) Federated ANN, federated LSTM and federated CNN-LSTM (multi-domain). We evaluate the performance of each of these deep learning models trained over a commercial network operator dataset and investigate the pros and cons of different approaches for VNF auto-scaling. For the first approach, our results show that both MLP classifier and MLP regressor models have strong predicting capability for auto-scaling. However, MLP regressor outperforms MLP classifier in terms of accuracy. For the second approach (one-step prediction), CNN-LSTM performs the best for the QoS-prioritized objective and LSTM performs the best for the cost-prioritized objective. For the second approach (multi-step prediction), the encoder-decoder CNN-LSTM model outperforms the encoder-decoder LSTM model for both QoS and Cost prioritized objectives. For the third approach, both federated LSTM and federated CNN-LSTM models perform equally better than the federated ANN model. It was also noted that in general federated learning approaches performs poorly compared to centralized learning approaches. Secondly, we employ Integer Linear Programming (ILP) techniques to formulate and solve a joint user association and SFC placement problem, where each SFC represents a service requested by a user with end-to-end latency and data rate requirements. We also develop a comprehensive end-to-end latency model considering radio delay, backhaul network delay and SFC processing delay for 5G mobile networks. We evaluated the proposed model using simulations based on real-operator network topology and real-world latency values. Our results show that the average end-to-end latency reduces significantly when SFCs are placed at the ME hosts according to their latency and data rate demands. Furthermore, we propose an heuristic algorithm to address the issue of scalability in ILP, that can solve the above association/mapping problem in seconds rather than hours.Finally, we introduce lightMEC - a lightweight MEC platform for deploying mobile edge computing functionalities which allows hosting of low-latency and bandwidth-intensive applications at the network edge. Measurements conducted over a real-life test demonstrated that lightMEC could actually support practical MEC applications without requiring any change to existing mobile network nodes' functionality in the access and core network segments. The significant benefits of adopting the proposed architecture are analyzed based on a proof-of-concept demonstration of the content caching use case. Furthermore, we introduce the AI-driven Kubernetes orchestration prototype that we implemented by leveraging the lightMEC platform and assess the performance of the proposed deep learning models (from stage 1) in an experimental setup. The prototype evaluations confirm the simulation results achieved in stage 1 of the thesis.
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Alleg, Abdelhamid. "Service Function Placement and Chaining in Network Function Virtualization Environments." Thesis, Bordeaux, 2019. http://www.theses.fr/2019BORD0117.

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L'émergence de la technologie de virtualisation des fonctions réseau (NFV) a suscité un vif intérêt autour de la conception, la gestion et le déploiement de services réseau de manière flexible, automatisée et indépendante du fournisseur. La mise en œuvre de la technologie NFV devrait être une solution profitable pour les fournisseurs de services et les clients. Cependant, ce changement de paradigme, amorcé par NFV, nécessite un abandon progressif des services réseau fournis à travers des équipements dédiés. En contrepartie, un environnement totalement ou partiellement virtualisé est proposé pour instancier dynamiquement et à la demande des modules logiciels appelés fonctions de réseau virtuelles (VNF). Cette évolution soulève un ensemble de défis liés au déploiement et à l'exploitation de services, tels que l'orchestration et la gestion, la résilience des services, le contrôle de la qualité de service (QoS), l’approvisionnement des ressources, etc. En outre, la question centrale à résoudre dans le contexte NFV est la suivante : « comment placer et chaîner effacement des fonctions virtuelles d’un service afin de fournir un niveau de qualité demandé par le client tout en optimisant l'utilisation des ressources par le fournisseur de services ? ”.Ainsi, cette thèse étudie la problématique du placement et du chaînage des VNF en tenant compte de certaines exigences de service telles que le délai de bout en bout, la disponibilité du service et la consommation d'énergie, et propose un ensemble d'algorithmes et de mécanismes visant à optimiser le déploiement des services demandés/fournis. Nos contributions dans cette thèse sont triples. Premièrement, nous proposons deux algorithmes de placement et de chaînage de VNF sensibles au délai de bout-en-bout pour des applications temps-réel. Les algorithmes proposés visent à respecter le délai approprié de bout-en-bout qui dépend du service déployé (exemples : VoIP, Streaming, etc.). Deuxièmement, nous présentons une analyse comparative de la disponibilité des services et nous proposons deux mécanismes de placement et de chaînage de VNF pour garantir un niveau prédéfini de disponibilité. L’objectif est de fournir des services résilients en ajustant avec précision les paramètres du schéma de protection (nombre, type, emplacement et taille des instances VNF) nécessaires pour atteindre ce niveau de disponibilité en dépit des défaillances du réseau. Enfin, nous proposons une architecture générale qui explore la possibilité d’étendre le paradigme de la virtualisation à l’Internet des objets (IoT). À cette fin, nous définissons un mécanisme de placement et de chaînage respectant les contraintes énergétiques pour des services IoT. Notre architecture propose de découpler et de virtualiser les fonctionnalités inhérentes à un objet connecté de l’équipement IoT physique. En étendant NFV au domaine IoT, notre solution ouvre de nouvelles perspectives d’application en supportant de nouveaux cas d’usages
The emergence of Network Function Virtualization (NFV) technology has aroused keen interest to design, manage and deploy network services in a flexible, automated and vendor-agnostic manner. Implementing NFV technology is expected to be a win-win solution for both service providers and costumers. However, this paradigm shift, sparked by NFV, calls for a progressive abandon of network services that are provided as hardware appliance and rather it proposes a fully or partially virtualized environment that offers software modules called Virtual Network Functions (VNFs). This shift rises a set of challenges related to service deployment and operation such as orchestration and management, service resiliency, Quality of Service (QoS) and resource provisioning among others. Furthermore, the core question that needs to be solved within NFV context is “What is the best way to place and chain VNFs that form a service in order to meet Service Level Agreement requirements (costumer side) while optimizing resource usage (service provider side)?”.This thesis investigates the problem of VNF Placement and Chaining considering service requirements such as end-to-end delay, service availability and energy consumption and proposes a set of algorithms and mechanisms that aim to achieve an optimized deployment of the requested/provided services. Our contributions in this thesis are threefold. First, we propose a delay-aware Placement and Chaining algorithms for delay-sensitive applications over NFV networks. The proposed algorithms aim to meet the appropriate end-to-end delay defined according to the deployed service (VoIP, Streaming, etc.). Second, we provide a comprehensive service availability benchmarking and we propose two availability-aware mechanisms for VNFs chain. The aim is to provide resilient service provisioning by fine-tuning the parameters of the protection scheme (the number, the type, the placement and the size of the spare instances) needed to reach a predefined availability level, despite network failures. Finally, we propose a framework architecture that explores the possibility to extend the virtualization paradigm to Internet of Things (IoT). Toward this end, we define an energy-aware Placement and Chaining for IoT services where inherent IoT functionalities are decoupled from specific dedicated IoT devices and instantiated on-demand. By bringing together NFV and IoT paradigms, this extension opens new perspectives and push toward designing new use cases
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Luizelli, Marcelo Caggiani. "Scalable cost-efficient placement and chaining of virtual network functions." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2017. http://hdl.handle.net/10183/169337.

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A Virtualização de Funções de Rede (NFV – Network Function Virtualization) é um novo conceito arquitetural que está remodelando a operação de funções de rede (e.g., firewall, gateways e proxies). O conceito principal de NFV consiste em desacoplar a lógica de funções de rede dos dispositivos de hardware especializados e, desta forma, permite a execução de imagens de software sobre hardware de prateleira (COTS – Commercial Off-The-Shelf). NFV tem o potencial para tornar a operação das funções de rede mais flexíveis e econômicas, primordiais em ambientes onde o número de funções implantadas pode chegar facilmente à ordem de centenas. Apesar da intensa atividade de pesquisa na área, o problema de posicionar e encadear funções de rede virtuais (VNF – Virtual Network Functions) de maneira escalável e com baixo custo ainda apresenta uma série de limitações. Mais especificamente, as estratégias existentes na literatura negligenciam o aspecto de encadeamento de VNFs (i.e., objetivam sobretudo o posicionamento), não escalam para o tamanho das infraestruturas NFV (i.e., milhares de nós com capacidade de computação) e, por último, baseiam a qualidade das soluções obtidas em custos operacionais não representativos. Nesta tese, aborda-se o posicionamento e o encadeamento de funções de rede virtualizadas (VNFPC – Virtual Network Function Placement and Chaining) como um problema de otimização no contexto intra- e inter-datacenter. Primeiro, formaliza-se o problema VNFPC e propõe-se um modelo de Programação Linear Inteira (ILP) para resolvêlo. O objetivo consiste em minimizar a alocação de recursos, ao mesmo tempo que atende aos requisitos e restrições de fluxo de rede. Segundo, aborda-se a escalabilidade do problema VNFPC para resolver grandes instâncias do problema (i.e., milhares de nós NFV). Propõe-se um um algoritmo heurístico baseado em fix-and-optimize que incorpora a meta-heurística Variable Neighborhood Search (VNS) para explorar eficientemente o espaço de solução do problema VNFPC. Terceiro, avalia-se as limitações de desempenho e os custos operacionais de estratégias típicas de aprovisionamento ambientes reais de NFV. Com base nos resultados empíricos coletados, propõe-se um modelo analítico que estima com alta precisão os custos operacionais para requisitos de VNFs arbitrários. Quarto, desenvolve-se um mecanismo para a implantação de encadeamentos de VNFs no contexto intra-datacenter. O algoritmo proposto (OCM – Operational Cost Minimization) baseia-se em uma extensão da redução bem conhecida do problema de emparelhamento ponderado (i.e., weighted perfect matching problem) para o problema de fluxo de custo mínimo (i.e., min-cost flow problem) e considera o desempenho das VNFs (e.g., requisitos de CPU), bem como os custos operacionais estimados. Os resultados alcaçados mostram que o modelo ILP proposto para o problema VNFPC reduz em até 25% nos atrasos fim-a-fim (em comparação com os encadeamentos observados nas infra-estruturas tradicionais) com um excesso de provisionamento de recursos aceitável – limitado a 4%. Além disso, os resultados evidenciam que a heurística proposta (baseada em fix-and-optimize) é capaz de encontrar soluções factíveis de alta qualidade de forma eficiente, mesmo em cenários com milhares de VNFs. Além disso, provê-se um melhor entendimento sobre as métricas de desempenho de rede (e.g., vazão, consumo de CPU e capacidade de processamento de pacotes) para as estratégias típicas de implantação de VNFs adotadas infraestruturas NFV. Por último, o algoritmo proposto no contexto intra-datacenter (i.e. OCM) reduz significativamente os custos operacionais quando comparado aos mecanismos de posicionamento típicos uti
Network Function Virtualization (NFV) is a novel concept that is reshaping the middlebox arena, shifting network functions (e.g. firewall, gateways, proxies) from specialized hardware appliances to software images running on commodity hardware. This concept has potential to make network function provision and operation more flexible and cost-effective, paramount in a world where deployed middleboxes may easily reach the order of hundreds. Despite recent research activity in the field, little has been done towards scalable and cost-efficient placement & chaining of virtual network functions (VNFs) – a key feature for the effective success of NFV. More specifically, existing strategies have neglected the chaining aspect of NFV (focusing on efficient placement only), failed to scale to hundreds of network functions and relied on unrealistic operational costs. In this thesis, we approach VNF placement and chaining as an optimization problem in the context of Inter- and Intra-datacenter. First, we formalize the Virtual Network Function Placement and Chaining (VNFPC) problem and propose an Integer Linear Programming (ILP) model to solve it. The goal is to minimize required resource allocation, while meeting network flow requirements and constraints. Then, we address scalability of VNFPC problem to solve large instances (i.e., thousands of NFV nodes) by proposing a fixand- optimize-based heuristic algorithm for tackling it. Our algorithm incorporates a Variable Neighborhood Search (VNS) meta-heuristic, for efficiently exploring the placement and chaining solution space. Further, we assess the performance limitations of typical NFV-based deployments and the incurred operational costs of commodity servers and propose an analytical model that accurately predict the operational costs for arbitrary service chain requirements. Then, we develop a general service chain intra-datacenter deployment mechanism (named OCM – Operational Cost Minimization) that considers both the actual performance of the service chains (e.g., CPU requirements) as well as the operational incurred cost. Our novel algorithm is based on an extension of the well-known reduction from weighted matching to min-cost flow problem. Finally, we tackle the problem of monitoring service chains in NFV-based environments. For that, we introduce the DNM (Distributed Network Monitoring) problem and propose an optimization model to solve it. DNM allows service chain segments to be independently monitored, which allows specialized network monitoring requirements to be met in a efficient and coordinated way. Results show that the proposed ILP model for the VNFPC problem leads to a reduction of up to 25% in end-to-end delays (in comparison to chainings observed in traditional infrastructures) and an acceptable resource over-provisioning limited to 4%. Also, we provide strong evidences that our fix-and-optimize based heuristic is able to find feasible, high-quality solutions efficiently, even in scenarios scaling to thousands of VNFs. Further, we provide indepth insights on network performance metrics (such as throughput, CPU utilization and packet processing) and its current limitations while considering typical deployment strategies. Our OCM algorithm reduces significantly operational costs when compared to the de-facto standard placement mechanisms used in Cloud systems. Last, our DNM model allows finer grained network monitoring with limited overheads. By coordinating the placement of monitoring sinks and the forwarding of network monitoring traffic, DNM can reduce the number of monitoring sinks and the network resource consumption (54% lower than a traditional method).
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Visser, Riaan. "Operational-cost optimisation and cost management in the sourcing and supply chain : a conceptual framework for a medium-sized service company without a central procurement function." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/997.

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Thesis (MBA (Business Management))--Stellenbosch University, 2009.
ENGLISH ABSTRACT: A typical medium-sized service company in South Africa faces definite challenges and misses opportunities in optimising and managing its operational expenses in its sourcing and supply chain. Medium-sized companies generally do not have the benefit of sophisticated in-house procurement divisions and extensive buying power but they still have to optimise their expenses in order to ensure maximum profitability and business longevity. The study addresses these challenges and opportunities by developing and proposing a framework for a typical medium-sized service company that does not have a central procurement function related to the cost optimisation and management of the identified sourcing and supply-chain elements. The research process entails the development of a conceptual framework developed from literature analysis and a representational practical environment as well as the testing, reviewing and validating of the test implementation of the framework. The results flowing from the testing and implementation of the framework are excluded from the research project. The results are displayed in the form of a summary of specific relevant information around each framework element as well as a conceptual framework. Recommendations are made in relation to the implementation and practical adaptation of the framework. It is concluded that a medium-sized service company can successfully optimise and manage its costs in the sourcing and supply-chain elements in the absence of a central procurement function. This requires the effective implementation of the developed framework, which was adapted from sophisticated larger companies. Implementation and the measurement process need to be driven or, preferably, conducted by the medium-sized company owner or management. Buy-in of the framework and the processes around it needs to be obtained from employees, suppliers and other stakeholders.
AFRIKAANSE OPSOMMING: ’n Tipiese mediumgrootte diensverskaffingsonderneming in Suid-Afrika staar spesifieke uitdagings in die gesig en ontbeer geleenthede met betrekking tot die optimalisering en bestuur van die bedryfsuitgawes in sy aankoop- en verskaffingsketting. Mediumgrootte ondernemings beskik in die algemeen nie oor die voordeel van ’n gesofistikeerde interne aankoopafdeling en groot aankoopkrag nie, maar hierdie ondernemings moet nog steeds hulle koste-uitgawes optimaliseer in die nastreef van maksimale wins en besigheidsukses. Die navorsingstudie neem hierdie uitdagings en geleenthede onder die loep deur die ontwikkeling en aanbeveling van ’n raamwerk vir ’n tipiese mediumgrootte diensverskaffingsonderneming wat nie oor ’n sentrale interne aankoopafdeling beskik nie. Die raamwerk is gebaseer op koste-optimalisering en -bestuur van die geïdentifiseerde aankoop- en verskaffingskettingelemente. Die navorsingsproses behels die ontwikkeling van ’n konseptuele raamwerk deur literatuuranalise en ’n verteenwoordigende praktiese omgewing, sowel as die toetsing, hersiening en geldigverklaring van die raamwerk tydens die toets-implementering daarvan in die praktiese omgewing. Die resultate van die toets en implementering van die raamwerk vorm nie deel van hierdie studie nie. Die navorsingsresultate word ten toon gestel in die vorm van ’n opsomming van die relevante raamwerkelemente sowel as ’n ontwikkelde raamwerk. Aanbevelings ten opsigte van die implementering en praktiese aanpassing van die raamwerk word dan gemaak. Die gevolgtrekking word gemaak dat ’n mediumgrootte diensverskaffingsonderneming wel in die afwesigheid van ’n sentrale interne aankoopafdeling sy kostes in die aankoop- en verskaffingsketting suksesvol kan optimaliseer en bestuur. Dit kan gedoen word deur die doeltreffende implementering en aanwending van die ontwikkelde raamwerk wat vanaf groter ondernemings aangepas is. Die raamwerk se implementering- en metingsproses moet deur die eienaar of bestuur van die mediumgrootte onderneming gelei, of verkieslik uitgevoer, word. Die werknemers, verskaffers en ander belanghebbendes se ondersteuning vir die raamwerk en gepaardgaande prosesse is baie belangrik vir die implementering en sukses van die raamwerk.
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6

WANG, YUN, and 王云. "Adaptive Placement and Routing for Service Function Chains with Deadlines in Software-Defined Networks." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/8zw594.

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碩士
國立臺灣科技大學
資訊工程系
106
Software-defined network(SDN) is shifting data communication in network toward more centralized control. The controller manages all necessary information and decides the transit path through commands. Middleboxes such as firewalls, decryptors, load balancers, etc., are functional hardware devices that are　indispensable in the cloud　and in corporate networks, but are expensive and difficult to maintain. The availability of virtual machines enables dynamic placement of virtual network functions(VNFs) on demand, it can reduce a large number of manual configuration processes, introduce flexibility, and increase deployment efficiency. Service requirements may need more than one VNF. Instead, it may need to traverse a set of sequential functional services called Service Function Chain (SFC). For example: first through the firewall, then through the encryption device, and finally through the decryption device, if these functional services are unordered, it will affect　the correctness of the entire service requirements. A key challenge is to efficiently route service function chains and place processing functions in a network under operational constraints. We must overcome two challenges: (1) determining a flow path that traverses suitable processing nodes in the correct order to meet the requirements of a given service chain, and (2) considering network load and other dynamic characteristics when routing through 　existing VNFs. We present a method to solve the node-constrained service chain routing problem in a software-defined network. The main idea is to transform the network representation to a layered graph that considers processing steps and allows the use of conventional shortest path algorithms, such as Dijkstra’s algorithm, to solve the problem. We are not only pursuing the high efficiency of acceptance ratio, but also 　taking into account the execution time of the algorithm.
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7

Hsiao, Chung-Che, and 蕭崇哲. "Placement of Virtual Network Functions Using the Relation of Virtual Network Functions in Service Chains." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/87018831856926973824.

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碩士
國立清華大學
資訊工程學系
104
Network function virtualization (NFV) has changed the traditional usage of network functions from hardware appliances to software implementation. Placement of virtual network functions (VNFs) has become a fundamental problem in NFV. In this study, relation in VNFs, including dependency and changes of flow size, would be important factors in placement of VNFs onto virtual machines on servers. Metric embedding is adopted to combine the relation of VNFs and virtual machines on network servers. The structures shown in service chains are seized by embedding algorithm and thus reflect the result on placement of VNFs on the network. In the simulation section, the proposed technique is evaluated and performs well in test cases, showing that the proposed technique gives a fine solution to VNF placement problem.
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8

Hsieh, Cheng-Husan, and 謝政軒. "Network-aware Service Function Chaining Placement in a Data Center." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/48fqrc.

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碩士
國立交通大學
網路工程研究所
104
Network function virtualization (NFV) has drawn much attention in recent years; some network functions used to be deployed on the specific hardware have become virtualized instances on general servers to achieve more scalability and flexibility. In data center, service function chaining (SFC) makes different workflow traverse different network functions in a specific ordering to provide different levels of the service for its customer. Since the distance between any adjacent network functions in a service chain will decide the total bandwidth consumption for that chain, the placement of the virtualized network functions in data center becomes a major issue. In this thesis, we treat this placement problem as multi-layer bin packing problem and formulate it as Integer Linear Programming. We propose three algorithms for different network topologies. Partition Best-fit is designed for the topology-unaware, and Multi-layer Best-fit and Multi-layer Worst-fit are designed for the tree-like network topology. The experiment results show that both Partition Best-fit and Multi-layer Best-fit can reduce bandwidth consumption in 15% while only increase a little number of used servers in 1% compare to traditional Best-fit algorithm.
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Shuo-San, Shih, and 史碩三. "A Service Function Cloud Platform with Hybrid NFV Environment Placement Strategy." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/3344vd.

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Abstract:
碩士
國立中央大學
資訊工程學系
105
In recent years, the network functions virtualization (NFV) was proposed to separate network functions from the underlying hardware to provide value-added service functions with software. The concept of service function chain (SFC) architecture has also been proposed, which allow traffic pass through some value-added network functions between end-to-end services. The placement of the service functions in data centers significantly affects the performance of SFC. We study the service function placement problem in hybrid NFV environment, which is an alternative plan during the transition from traditional networks to NFV networks in data centers. We present GASFP, a high-performance approach for optimizing service function placement and service chaining in hybrid NFV environment. GASFP combine GA (Genetic Algorithm) and Greedy best-first search algorithm to reduce the waste of data center computation resource for providing SFC services and find a good solution to slow down the growth of delay from unsuitable service function placement. Simulation results show that when compared with other 3 algorithms: BINPacking, GKMSFP and VCD, GASFP has the best performance of average delay and VNF placement cost no matter in hybrid NFV environment or pure NFV environment. We also implement a service function cloud platform and a SFC steering mechanism named NSHSFC in XenServer to verify our works are more comprehensive and realistic than the former works. Keyword: Software-defined Networking; Service Function Chain; Network Function Virtualization; service function placement; genetic algorithm
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Chou, Hsin-Yao, and 周新堯. "SDN-based Network Resource Management with Service Function Chain." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/qrnak9.

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Abstract:
碩士
國立中央大學
資訊工程學系
103
In recent years, as growth of the cloud computing technology, more demand for network resources allocation and management of value-added services are appeared. The new concept of network service architecture, Service Function Chain (SFC), has been proposed. The specification of various vendor equipments is unique, prompts the traditional network to change. The purpose of Software-Defined Network (SDN) is to change the physical, complex network into a virtual, programmable and open network architecture. OpenFlow protocol is the most common technology for SDN architecture. The Network management can be more flexible by the centralized and programable property of OpenFlow. VLAN and OpenFlow based Service Function Chain (VOFSFC) and services deployment mechanism are proposed to improve the flexibility of the network service deployment and reduce the consumption of network resources. VOFSFC use the virtual LAN (VLAN) technology to develop VLAN of Path adoption mechanism. It can identify different requirements of network traffic, steer/deliver packets to service functions and record information of the traffic. In addition, consider the placement of service functions, develop and propose GARCH and K-Means Service Function Placement (GKMSFP) mechanism to cluster and deploy service functions for reduce the load of network resources. The results shows the proposed VOPSFC system can provide high elasticity and flexibility for the network management, and the proposed GKMSFP mechanism can reduce 45.6% network resource consumption from the general situation which without cluster mechanism. It shows that mechanisms can reduce the traffic load of network in the SFC system.
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Book chapters on the topic "Service Function Chain Placement"

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Chen, Weihan, Xia Yin, Zhiliang Wang, Xingang Shi, and Jiangyuan Yao. "Placement and Routing Optimization Problem for Service Function Chain: State of Art and Future Opportunities." In Communications in Computer and Information Science, 176–88. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8101-4_17.

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Gao, Lynn, Yutian Chen, and Bin Tang. "Service Function Chain Placement in Cloud Data Center Networks: A Cooperative Multi-agent Reinforcement Learning Approach." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 291–309. Cham: Springer Nature Switzerland, 2022. http://dx.doi.org/10.1007/978-3-031-23141-4_22.

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Kutiel, Gilad, and Dror Rawitz. "Service Chain Placement in SDNs." In Algorithmic Aspects of Cloud Computing, 27–40. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74875-7_3.

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Grigorjew, Alexej, Stanislav Lange, Thomas Zinner, and Phuoc Tran-Gia. "Performance Benchmarking of Network Function Chain Placement Algorithms." In Lecture Notes in Computer Science, 83–98. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74947-1_6.

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Zhang, Shaojun, Yutong Ji, Yufan Cheng, Ying Wang, and Peng Yu. "Resource-Aware Reliability Assurance of Service Function Chain." In Proceedings of the 11th International Conference on Computer Engineering and Networks, 1500–1508. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-6554-7_165.

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Ocampo, Andrés F., Juliver Gil-Herrera, Pedro H. Isolani, Miguel C. Neves, Juan F. Botero, Steven Latré, Lisandro Zambenedetti, Marinho P. Barcellos, and Luciano P. Gaspary. "Optimal Service Function Chain Composition in Network Functions Virtualization." In Lecture Notes in Computer Science, 62–76. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-60774-0_5.

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Liu, Ziyu, Zeming Li, Chengchao Liang, and Zhanjun Liu. "Routing and Resource Allocation for Service Function Chain in Service-Oriented Network." In Communications and Networking, 465–80. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99200-2_35.

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Shi, Zhan, Zanhong Wu, and Ying Zeng. "A Method of Service Function Chain Arrangement for Load Balancing." In Proceedings of the 9th International Conference on Computer Engineering and Networks, 35–42. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3753-0_4.

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Kang, Zhongmiao, Yijie Li, Peiming Zhang, Donghai Huang, and Shaoyong Guo. "Service Function Chain Reliability Improvement Algorithm Based on Resource Characteristics." In Lecture Notes in Electrical Engineering, 206–12. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-6901-0_23.

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Bittar, Abdullah, Ziqiang Wang, Amir Aghasharif, Changcheng Huang, Gauravdeep Shami, Marc Lyonnais, and Rodney Wilson. "Service Function Chaining Design & Implementation Using Network Service Mesh in Kubernetes." In Supercomputing Frontiers, 121–40. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10419-0_8.

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AbstractService Function Chaining (SFC) in a cloud-native environment is becoming essential as more users move towards clouds today. Cloud-native environments utilize container-based microservices to provide software solutions. Integrating SFC with container-based microservices introduces new challenges. This paper exploited Network Service Mesh (NSM) framework features to create a service function chain on a multi-node Kubernetes cluster. We focus on the design and implementation of SFC in Kubernetes using NSM. Also, we deployed our custom-built containers in the Kubernetes cluster to create a service function chain. Hence, we demonstrate how an SFC is designed in a cloud-native environment rather than a traditional NFV/SDN approach. Furthermore, to evaluate the performance, we compare different frameworks that support SFC in Kubernetes, highlighting the advantage and disadvantages of each framework.
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Conference papers on the topic "Service Function Chain Placement"

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Kouah, Riad, Abdelhamid Alleg, Abir Laraba, and Toufik Ahmed. "Energy-Aware Placement for IoT-Service Function Chain." In 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). IEEE, 2018. http://dx.doi.org/10.1109/camad.2018.8515003.

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Hmaity, Ali, Marco Savi, Francesco Musumeci, Massimo Tornatore, and Achille Pattavina. "Virtual Network Function placement for resilient Service Chain provisioning." In 2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM). IEEE, 2016. http://dx.doi.org/10.1109/rndm.2016.7608294.

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Yin, Xiaohan, Bo Cheng, Meng Wang, and Junliang Chen. "Availability-aware Service Function Chain Placement in Mobile Edge Computing." In 2020 IEEE World Congress on Services (SERVICES). IEEE, 2020. http://dx.doi.org/10.1109/services48979.2020.00028.

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Harutyunyan, Davit, Nashid Shahriar, Raouf Boutaba, and Roberto Riggio. "Latency-Aware Service Function Chain Placement in 5G Mobile Networks." In 2019 IEEE Conference on Network Softwarization (NetSoft). IEEE, 2019. http://dx.doi.org/10.1109/netsoft.2019.8806646.

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Shang, Xiaojun, Zhenhua Liu, and Yuanyuan Yang. "Network Congestion-aware Online Service Function Chain Placement and Load Balancing." In ICPP 2019: 48th International Conference on Parallel Processing. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3337821.3337850.

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Savi, Marco, Massimo Tornatore, and Giacomo Verticale. "Impact of processing costs on service chain placement in network functions virtualization." In 2015 IEEE Conference on Network Function Virtualization and Software-Defined Networks (NFV-SDN). IEEE, 2015. http://dx.doi.org/10.1109/nfv-sdn.2015.7387426.

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Chai, Hua, Jiao Zhang, Zenan Wang, Jiaming Shi, and Tao Huang. "A Parallel Placement Approach for Service Function Chain Using Deep Reinforcement Learning." In 2019 IEEE 5th International Conference on Computer and Communications (ICCC). IEEE, 2019. http://dx.doi.org/10.1109/iccc47050.2019.9064448.

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Xu, Yansen, and Ved P. Kafle. "Optimal Service Function Chain Placement Modeling for Minimizing Setup and Operation Cost." In 2018 IEEE 7th International Conference on Cloud Networking (CloudNet). IEEE, 2018. http://dx.doi.org/10.1109/cloudnet.2018.8549288.

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Wang, Meng, Bo Cheng, Wendi Feng, and Junliang Chen. "An Efficient Service Function Chain Placement Algorithm in a MEC-NFV Environment." In GLOBECOM 2019 - 2019 IEEE Global Communications Conference. IEEE, 2019. http://dx.doi.org/10.1109/globecom38437.2019.9013235.

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Xu, Yansen, and Ved P. Kafle. "A Delay-Aware Service Function Chain Placement Scheme Based on Dynamic Programming." In 2018 IEEE International Symposium on Local and Metropolitan Area Networks (LANMAN). IEEE, 2018. http://dx.doi.org/10.1109/lanman.2018.8475115.

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