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Статті в журналах з теми "Service Function Chain Placement"

Автор: Grafiati

Опубліковано: 11 березня 2023

Оновлено: 25 липня 2025

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1

Khoshkholghi, Mohammad Ali, Michel Gokan Khan, Kyoomars Alizadeh Noghani, et al. "Service Function Chain Placement for Joint Cost and Latency Optimization." Mobile Networks and Applications 25, no. 6 (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 envi

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2

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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Анотація:

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 w

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3

Abdelaal, Marwa A., Gamal A. Ebrahim, and Wagdy R. Anis. "Efficient Placement of Service Function Chains in Cloud Computing Environments." Electronics 10, no. 3 (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 con

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4

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 (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, consist

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5

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 (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 distr

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6

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 (2019): 1638–50. http://dx.doi.org/10.1109/tnsm.2019.2933872.

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7

Pandey, Abhishek Kumar, and Sarvpal Singh. "Service Chain Placement by Using an African Vulture Optimization Algorithm Based VNF in Cloud-Edge Computing." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 12 (December 29, 2023): e31509. http://dx.doi.org/10.14201/adcaij.31509.

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The use of virtual network functions (VNFs) enables the implementation of service function chains (SFCs), which is an innovative approach for delivering network services. The deployment of service chains on the actual network infrastructure and the establishment of virtual connections between VNF instances are crucial factors that significantly impact the quality of network services provided. Current research on the allocation of vital VNFs and resource constraints on the edge network has overlooked the potential benefits of employing SFCs with instance reuse. This strategy offers significant

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8

Li, Wei, Yuan Jiang, Xiaoliang Zhang, et al. "Reliability Assurance Dynamic SSC Placement Using Reinforcement Learning." Information 13, no. 2 (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 s

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9

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 (2021): 3021–36. http://dx.doi.org/10.1109/tnsm.2021.3086977.

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10

Wang, Xi, Shuo Shi, and Chenyu Wu. "Research on Service Function Chain Embedding and Migration Algorithm for UAV IoT." Drones 8, no. 4 (2024): 117. http://dx.doi.org/10.3390/drones8040117.

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This paper addresses the challenge of managing service function chaining (SFC) in an unmanned aerial vehicle (UAV) IoT, a dynamic network that integrates UAVs and IoT devices for various scenarios. To enhance the service quality and user experience of the UAV IoT, network functions must be flexibly configured and adjusted based on varying service demands and network situations. This paper presents a model for calculating benefits and an agile algorithm for embedding and migrating SFC based on particle swarm optimization (PSO). The model takes into account multiple factors such as SFC quality,

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11

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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12

Manzanares-Lopez, Pilar, Juan Pedro Muñoz-Gea, and Josemaria Malgosa-Sanahuja. "VNF Placement for Service Function Chains with Strong Low-Delay Restrictions in Edge Computing Networks." Applied Sciences 10, no. 18 (2020): 6573. http://dx.doi.org/10.3390/app10186573.

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Анотація:

The edge computing paradigm, allowing the location of network services close to end users, defines new network scenarios. One of them considers the existence of micro data centers, with reduced resources but located closer to service requesters, to complement remote cloud data centers. This hierarchical and geo-distributed architecture allows the definition of different time constraints that can be taken into account when mapping services into data centers. This feature is especially useful in the Virtual Network Function (VNF) placement problem, where the network functions composing a Service

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13

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 (2021): 4134–50. http://dx.doi.org/10.1109/tnsm.2021.3127685.

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14

Mechtri, Marouen, Chaima Ghribi, and Djamal Zeghlache. "A Scalable Algorithm for the Placement of Service Function Chains." IEEE Transactions on Network and Service Management 13, no. 3 (2016): 533–46. http://dx.doi.org/10.1109/tnsm.2016.2598068.

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15

Zu, Jiachen, Guyu Hu, Jiajie Yan, and Siqi Tang. "A community detection based approach for Service Function Chain online placement in data center network." Computer Communications 169 (March 2021): 168–78. http://dx.doi.org/10.1016/j.comcom.2021.01.014.

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16

XU, Yansen, and Ved P. KAFLE. "A Mathematical Model and Dynamic Programming Based Scheme for Service Function Chain Placement in NFV." IEICE Transactions on Information and Systems E102.D, no. 5 (2019): 942–51. http://dx.doi.org/10.1587/transinf.2018ntp0015.

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17

de Freitas Bezerra, Diego, Guto Leoni Santos, Élisson da Silva Rocha, et al. "Multi-objective Service Function Chain placement in 5G cellular networks based on meta-heuristic approach." Simulation Modelling Practice and Theory 133 (May 2024): 102927. http://dx.doi.org/10.1016/j.simpat.2024.102927.

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18

Wu, Xing, Jing Duan, Mingyu Zhong, Peng Li, and Jianjia Wang. "VNF Chain Placement for Large Scale IoT of Intelligent Transportation." Sensors 20, no. 14 (2020): 3819. http://dx.doi.org/10.3390/s20143819.

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Анотація:

With the advent of the Internet of things (IoT), intelligent transportation has evolved over time to improve traffic safety and efficiency as well as to reduce congestion and environmental pollution. However, there are some challenging issues to be addressed so that it can be implemented to its full potential. The major challenge in intelligent transportation is that vehicles and pedestrians, as the main types of edge nodes in IoT infrastructure, are on the constant move. Hence, the topology of the large scale network is changing rapidly over time and the service chain may need reestablishment

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19

Elagin, Vasily S., Alexander V. Bogachev, and Ilya A. Belozertsev. "Modeling the estimation of end-to-end packet latency for a chain of NFV nodes in 5G networks." T-Comm 16, no. 3 (2022): 23–30. http://dx.doi.org/10.36724/2072-8735-2022-16-3-23-30.

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It is expected that future communication networks will provide configurable delay-sensitive types of services (for example, streaming video, machine interaction). To support a variety of applications and use cases of servers providing various functions, you can use network function virtualization (NFV), which will be able to provide flexible implementation and placement of configuration of the necessary network functions. This article analyzes the end-to-end packet latency (E2E) for multiple traffic flows passing through the chain of embedded virtual network functions (VNF) in fifth-generation

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20

Alharbe, Nawaf, Abeer Aljohani, and Mohamed Ali Rakrouki. "A Fuzzy Grouping Genetic Algorithm for Solving a Real-World Virtual Machine Placement Problem in a Healthcare-Cloud." Algorithms 15, no. 4 (2022): 128. http://dx.doi.org/10.3390/a15040128.

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Due to the large-scale development of cloud computing, data center electricity energy costs have increased rapidly. Energy saving has become a major research direction of virtual machine placement problems. At the same time, the multi-dimensional resources on the cloud should be used in a balanced manner in order to avoid resources waste. In this context, this paper addresses a real-world virtual machine placement problem arising in a Healthcare-Cloud (H-Cloud) of hospitals chain in Saudi Arabia, considering server power consumption and resource utilization. As a part of optimizing both object

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21

Ros, Seyha, Prohim Tam, Inseok Song, Seungwoo Kang, and Seokhoon Kim. "Handling Efficient VNF Placement with Graph-Based Reinforcement Learning for SFC Fault Tolerance." Electronics 13, no. 13 (2024): 2552. http://dx.doi.org/10.3390/electronics13132552.

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Network functions virtualization (NFV) has become the platform for decomposing the sequence of virtual network functions (VNFs), which can be grouped as a forwarding graph of service function chaining (SFC) to serve multi-service slice requirements. NFV-enabled SFC consists of several challenges in reaching the reliability and efficiency of key performance indicators (KPIs) in management and orchestration (MANO) decision-making control. The problem of SFC fault tolerance is one of the most critical challenges for provisioning service requests, and it needs resource availability. In this articl

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22

Magoula, Lina, Sokratis Barmpounakis, Ioannis Stavrakakis, and Nancy Alonistioti. "A genetic algorithm approach for service function chain placement in 5G and beyond, virtualized edge networks." Computer Networks 195 (August 2021): 108157. http://dx.doi.org/10.1016/j.comnet.2021.108157.

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23

Yu, Heng, Zhilong Zheng, Junxian Shen, et al. "Octans: Optimal Placement of Service Function Chains in Many-Core Systems." IEEE Transactions on Parallel and Distributed Systems 32, no. 9 (2021): 2202–15. http://dx.doi.org/10.1109/tpds.2021.3063613.

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24

SARRIGIANNIS, IOANNIS, Angelos Antonopoulos, Kostas Ramantas, Maria Efthymiopoulou, Luis Miguel Contreras, and Christos Verikoukis. "Cost-Aware Placement and Enhanced Lifecycle Management of Service Function Chains in a Multidomain 5G Architecture." Cost-Aware Placement and Enhanced Lifecycle Management of Service Function Chains in a Multidomain 5G Architecture 19, no. 4 (2022): 5006–20. https://doi.org/10.1109/TNSM.2022.3187314.

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Анотація:

Service providers highly rely on network softwarization for addressing the demanding use cases of the 5G verticals. In order for the 5G vertical scenarios to be seamlessly executed, where the coverage should be provided in large areas, the required infrastructure capacity and availability can only be supported by cross-operator cooperation. In this context, we employ a novel federated core-edge 5G architecture, where 5G vertical services are represented as service function chains (SFCs) and can be offered on the infrastructure owned either by the local operator or a foreign one. Furthermore, w

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25

Bolumole, Yemisi A., A. Michael Knemeyer, and Douglas M. Lambert. "The Customer Service Management Process." International Journal of Logistics Management 14, no. 2 (2003): 15–31. http://dx.doi.org/10.1108/09574090310806576.

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Customer service management is the supply chain management process that represents the firm's face to the customer. The process is the key point of contact for administering product and service agreements (PSAs) developed by customer teams as part of the customer relationship management process. The goal is to provide a single source of customer information, such as product availability, shipping dates and order status. Customer service management requires a real‐time system to respond to customer inquiries and facilitate order placement. In this paper, we describe the customer service managem

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26

Nogalski, Dariusz, Dallal Belabed, Alexandre Triollet, et al. "Critical Function Placement based on Service Chains in Multi-administrative Federated Networks." Journal of Communications Software and Systems 21, no. 1 (2025): 1–12. https://doi.org/10.24138/jcomss-2024-0117.

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27

Pham, Tuan-Minh, and Thi-Minh Nguyen. "Optimizing Traffic Engineering for Resilient Services in NFV-Based Connected Autonomous Vehicles." Sensors 21, no. 24 (2021): 8446. http://dx.doi.org/10.3390/s21248446.

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The massive amount of data generated daily by various sensors equipped with connected autonomous vehicles (CAVs) can lead to a significant performance issue of data processing and transfer. Network Function Virtualization (NFV) is a promising approach to improving the performance of a CAV system. In an NFV framework, Virtual Network Function (VNF) instances can be placed in edge and cloud servers and connected together to enable a flexible CAV service with low latency. However, protecting a service function chain composed of several VNFs from a failure is challenging in an NFV-based CAV system

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28

Ruiz, Lidia, Ramón Durán, Ignacio de Miguel, et al. "A Genetic Algorithm for VNF Provisioning in NFV-Enabled Cloud/MEC RAN Architectures." Applied Sciences 8, no. 12 (2018): 2614. http://dx.doi.org/10.3390/app8122614.

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5G technologies promise to bring new network and service capacities and are expected to introduce significant architectural and service deployment transformations. The Cloud-Radio Access Networks (C-RAN) architecture, enabled by the combination of Software Defined Networking (SDN), Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) technologies, play a key role in the development of 5G. In this context, this paper addresses the problems of Virtual Network Functions (VNF) provisioning (VNF-placement and service chain allocation) in a 5G network. In order to solve that problem

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29

Pei, Jianing, Peilin Hong, Kaiping Xue, and Defang Li. "Efficiently Embedding Service Function Chains with Dynamic Virtual Network Function Placement in Geo-Distributed Cloud System." IEEE Transactions on Parallel and Distributed Systems 30, no. 10 (2019): 2179–92. http://dx.doi.org/10.1109/tpds.2018.2880992.

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30

Wu, You, Hefei Hu, and Ziyi Zhang. "DRL-Based Fast Joint Mapping Approach for SFC Deployment." Electronics 14, no. 12 (2025): 2408. https://doi.org/10.3390/electronics14122408.

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The rapid development of Network Function Virtualization (NFV) enables network operators to deliver customized end-to-end services through Service Function Chains (SFCs). However, existing two-stage deployment strategies fail to jointly optimize the placement of Virtual Network Functions (VNFs) and the routing of service traffic, resulting in inefficient resource utilization and increased service latency. This study addresses the challenge of maximizing the acceptance rate of service requests under resource constraints and latency requirements. We propose DRL-FJM, a novel dynamic SFC joint map

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31

Cañete, Angel, Pinilla María Mercedes Amor, and Lidia Fuentes. "HADES: An NFV solution for energy-efficient placement and resource allocation in heterogeneous infrastructures." Journal of Network and Computer Applications 221 (October 21, 2023): 103764. https://doi.org/10.1016/j.jnca.2023.103764.

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Network Function Virtualization (NFV) aims to replace traditional network functions running in proprietary hardware with software instances (i.e., Virtual Network Functions, VNFs) embedded in general-purpose virtualization solutions. Aware that the transition to a fully virtualized network infrastructure will pay a high energy cost, especially in IoT systems composed of a myriad of devices, energy efficiency is one of the key innovative targets of future networks. Edge computing should be considered in IoT environments to save time and energy by processing data near the producer devices. Howev

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32

Thiruvasagam, Prabhu Kaliyammal, Abhishek Chakraborty, Abin Mathew, and C. Siva Ram Murthy. "Reliable Placement of Service Function Chains and Virtual Monitoring Functions With Minimal Cost in Softwarized 5G Networks." IEEE Transactions on Network and Service Management 18, no. 2 (2021): 1491–507. http://dx.doi.org/10.1109/tnsm.2021.3056917.

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33

Guo, Shuang, Yarong Du, and Liang Liu. "A Meta Reinforcement Learning Approach for SFC Placement in Dynamic IoT-MEC Networks." Applied Sciences 13, no. 17 (2023): 9960. http://dx.doi.org/10.3390/app13179960.

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In order to achieve reliability, security, and scalability, the request flow in the Internet of Things (IoT) needs to pass through the service function chain (SFC), which is composed of series-ordered virtual network functions (VNFs), then reach the destination application in multiaccess edge computing (MEC) for processing. Since there are usually multiple identical VNF instances in the network and the network environment of IoT changes dynamically, placing the SFC for the IoT request flow is a significant challenge. This paper decomposes the dynamic SFC placement problem of the IoT-MEC networ

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34

Qi Xu, Deyun Gao, Huachun Zhou, Bohao Feng, and Taixin Li. "OpenNSP: Open Network Service Provision for Mobile Networks." Research Briefs on Information and Communication Technology Evolution 3 (May 15, 2017): 42–52. http://dx.doi.org/10.56801/rebicte.v3i.43.

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Анотація:

In recent years, many innovative techniques are emerged for satisfying various user requirements,such as Software Definition Network (SDN) and Network Function Virtualization (NFV). However,the current solutions for network service provision still lack enough flexibility and openness thatresult in high expenditures and complexity. Thus, we propose an Open Network Service Provision(OpenNSP) solution in this paper, aiming to address the multi-domain problems of service functionchain outsourcing for mobile networks. Particularly, OpenNSP is based on IETF hierarchical servicefunction chaining (hSF

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35

Dalgkitsis, A., L.A. Garrido, F. Rezazadeh, et al. "SCHE2MA: Scalable, Energy-Aware, Multidomain Orchestration for Beyond-5G URLLC Services." IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 24, no. 7 (2023): 7653–63. https://doi.org/10.1109/TITS.2022.3202312.

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Анотація:

The evolution of Software-Defined Networking (SDN) and Network Function Virtualization (NFV) in the telecommunications industry have intensified the issues of network management at large scales. Dynamic service orchestration and adaptive resource allocation became a necessity for network operators to manage the rapid growth of users and data-intensive applications. The impact of network automation on energy consumption and overall operating costs is often overlooked. Guaranteeing strict performance constraints of Ultra-Reliable Low Latency Communication (URLLC) services while enhancing energy

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36

Djekic, Ilija, Dubravka Skunca, Ivan Nastasijevic, Vladimir Tomovic, and Igor Tomasevic. "Transformation of quality aspects throughout the chicken meat supply chain." British Food Journal 120, no. 5 (2018): 1132–50. http://dx.doi.org/10.1108/bfj-08-2017-0432.

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Анотація:

Purpose The purpose of this paper is to analyze perceptions of quality in the chicken meat supply chain. Design/methodology/approach This survey covered 74 different farms, slaughterhouses, meat processors, and retailers and 500 consumers, using two methods. From the farm to retail, analysis covered “customer – supplier” viewpoints in different stages of the supply chain. From the consumers to the farms, the quality function deployment method was used. Five houses of quality have been developed using the Delphi method to synthesize the opinions of experts. Findings Farm-slaughter comparison sh

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37

Gatzianas, Marios, Agapi Mesodiakaki, George Kalfas, et al. "Offline Joint Network and Computational Resource Allocation for Energy-Efficient 5G and beyond Networks." Applied Sciences 11, no. 22 (2021): 10547. http://dx.doi.org/10.3390/app112210547.

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In order to cope with the ever-increasing traffic demands and stringent latency constraints, next generation, i.e., sixth generation (6G) networks, are expected to leverage Network Function Virtualization (NFV) as an enabler for enhanced network flexibility. In such a setup, in addition to the traditional problems of user association and traffic routing, Virtual Network Function (VNF) placement needs to be jointly considered. To that end, in this paper, we focus on the joint network and computational resource allocation, targeting low network power consumption while satisfying the Service Func

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38

Garrich, Miquel, José Luis Romero-Gázquez, Francisco Javier Moreno-Muro, et al. "IT and Multi-layer Online Resource Allocation and Offline Planning in Metropolitan Networks." IEEE Journal of Lightwave Technology 99 (May 1, 2020): 1. https://doi.org/10.5281/zenodo.3981187.

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Metropolitan networks are undergoing a major technological breakthrough leveraging the capabilities of software-defined networking (SDN) and network function virtualization (NFV). NFV permits the deployment of virtualized network functions (VNFs) on commodity hardware appliances which can be combined with SDN flexibility and programmability of the network infrastructure. SDN/NFV-enabled networks require decision-making in two time scales: short-term online resource allocation and mid-to-long term offline planning. In this paper, we first tackle the dimensioning of SDN/NFV-enabled metropolitan

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Dinh, Ngoc-Thanh, and Younghan Kim. "An Efficient Availability Guaranteed Deployment Scheme for IoT Service Chains over Fog-Core Cloud Networks." Sensors 18, no. 11 (2018): 3970. http://dx.doi.org/10.3390/s18113970.

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High availability is one of the important requirements of many end-to-end services in the Internet of Things (IoT). This is a critical issue in network function virtualization (NFV) and NFV-enabled service function chaining (SFC) due to hard- and soft-ware failures. Thus, merely mapping primary VNFs is not enough to ensure high availability, especially for SFCs deployed over fog - core cloud networks due to resource limitations of fogs. As a result, additional protection schemes, like VNF redundancy deployments, are required to improve the availability of SFCs to meet predefined requirements.

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Munshi, Joy, Sumaya Sultana, Md Jahid Hassan, et al. "Attention model-driven MADDPG algorithm for delay and cost-aware placement of service function chains in 5G." Ad Hoc Networks 173 (June 2025): 103806. https://doi.org/10.1016/j.adhoc.2025.103806.

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Li, Jing, Weifa Liang, Zichuan Xu, Xiaohua Jia, and Wanlei Zhou. "Service Provisioning for Multi-source IoT Applications in Mobile Edge Computing." ACM Transactions on Sensor Networks 18, no. 2 (2022): 1–25. http://dx.doi.org/10.1145/3484200.

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We are embracing an era of Internet of Things (IoT). The latency brought by unstable wireless networks caused by limited resources of IoT devices seriously impacts the quality of services of users, particularly the service delay they experienced. Mobile Edge Computing (MEC) technology provides promising solutions to delay-sensitive IoT applications, where cloudlets (edge servers) are co-located with wireless access points in the proximity of IoT devices. The service response latency for IoT applications can be significantly shortened due to that their data processing can be performed in a loca

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Miquel, Garrich, Romero-Gázquez José-Luis, Moreno-Muro Francisco-Javier, et al. "IT and Multi-layer Online Resource Allocation and Offline Planning in Metropolitan Networks." Journal of Lightwave Technology 38, no. 12 (2020): 3190–99. https://doi.org/10.1109/JLT.2020.2990066.

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Анотація:

Metropolitan networks are undergoing a major technological breakthrough leveraging the capabilities of software-defined networking (SDN) and network function virtualization (NFV). NFV permits the deployment of virtualized network functions (VNFs) on commodity hardware appliances which can be combined with SDN flexibility and programmability of the network infrastructure. SDN/NFV-enabled networks require decision-making in two time scales: short-term online resource allocation and mid-to-long term offline planning . In this paper, we first tackle the dimensioning of SDN/NFV-enabled metropolitan

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43

R.Sudhakar, V.Ramkumar, S.Santhosh, J.Suganth, and D.Thirunavukkarasu. "ONE PASS PACKET STEERING IN SOFTWARE DEFINED DATA CENTERS." international journal of engineering technology and management sciences 7, no. 2 (2023): 494–501. http://dx.doi.org/10.46647/ijetms.2023.v07i02.057.

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Issue of service function chaining in a network is the focus of this paper. Currently, middle box placement in a network and packet steering through middle boxes are the two main problems associated with chaining services in a network—also known as service function chaining. We propose a One Pass Packet Steering (OPPS) method for use in multi-subscriber environments with the goal of reducing the total amount of time it takes for Users and Services to connect. We show a proof of idea execution utilizing imitations performed with Mininet. According to our findings, the end-to-end delay of subscr

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Kizimirov, Mikhail V., and Evgenii V. Chernyaev. "Analysis of the Factors of Spatial Placement of Logistics Facilities." Russian journal of regional studies 33, no. 1 (2025): 138–51. https://doi.org/10.15507/2413-1407.033.202501.138-151.

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Introduction. The topic of the study is relevant because it examines key aspects of society and the economy, the understanding of which helps to make informed decisions about the location of logistics facilities and contributes to the development of an effective and sustainable logistics system. The aim of the paper is to examine the spatial distribution of logistics facilities, to identify the factors that influence their location and to present the methodological foundations that determine such a distribution. Materials and Methods. The research analyzed scientific publications on the subjec

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Kutiel, Gilad, and Dror Rawitz. "Service chain placement in SDNs." Discrete Applied Mathematics 270 (November 2019): 168–80. http://dx.doi.org/10.1016/j.dam.2019.06.013.

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Umrao, Brajesh Kumar, and Dharmendar Kumar Yadav. "APVNFC: Adaptive Placement of Virtual Network Function Chains." Cybernetics and Information Technologies 23, no. 1 (2023): 59–74. http://dx.doi.org/10.2478/cait-2023-0003.

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Abstract Designing efficient and flexible approaches for placement of Virtual Network Function (VNF) chains is the main success of Network Function Virtualization (NFV). However, most current work considers the constant bandwidth and flow processing requirements while deploying the VNFs in the network. The constant (immutable) flow processing and bandwidth requirements become critical limitations in an NFV-enabled network with highly dynamic traffic flow. Therefore, bandwidth requirements and available resources of the Point-of-Presence (PoP) in the network change constantly. We present an ada

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Hmaity, Ali, Marco Savi, Francesco Musumeci, Massimo Tornatore, and Achille Pattavina. "Protection strategies for virtual network functions placement and service chains provisioning." Networks 70, no. 4 (2017): 373–87. http://dx.doi.org/10.1002/net.21782.

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Zhu, Kai, Chunming Wu, and Boyang Zhou. "Scheduling Reconfigurable Service Function Chain." Chinese Journal of Electronics 28, no. 6 (2019): 1244–49. http://dx.doi.org/10.1049/cje.2019.08.011.

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Tassiulas, Leandros. "Enabling Intelligent Services at the Network Edge." ACM SIGMETRICS Performance Evaluation Review 49, no. 1 (2022): 69–70. http://dx.doi.org/10.1145/3543516.3453912.

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The proliferation of novel mobile applications and the associated AI services necessitates a fresh view on the architecture, algorithms and services at the network edge in order to meet stringent performance requirements. Some recent work addressing these challenges is presented. In order to meet the requirement for low-latency, the execution of computing tasks moves form the cloud to the network edge, closer to the end-users. The joint optimization of service placement and request routing in dense mobile edge computing networks is considered. Multidimensional constraints are introduced to cap

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Jang, Insun, Dongeun Suh, Sangheon Pack, and Gyorgy Dan. "Joint Optimization of Service Function Placement and Flow Distribution for Service Function Chaining." IEEE Journal on Selected Areas in Communications 35, no. 11 (2017): 2532–41. http://dx.doi.org/10.1109/jsac.2017.2760162.

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