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Latin America networking Conference (LANC)

作者： Garcia, German Pinto-Roa, Diego P. Univ Nacl Asuncion San Lorenzo Paraguay

ISBN: (纸本)9781450394291

Communication trends demand services that require flexible multicast transmission with requirements for data processing functions at the network nodes. This challenge is achieved with software-defined networking (SDN) and network functions virtualization (NFV) technologies. In the multicast routing problem in NFV-SDN networks, the goal is to compute a multicast tree and the location of virtual network functions (VNFs) at nodes, satisfying the traffic demand and processing functions with the least possible resource. The traffic flow must pass through a VNF node before reaching a destination node. Since the problem has high computational complexity and current proposals consider only one type of virtual function in all demands, the development of scalable solutions for multiple sessions with different virtual functions is necessary. This paper addresses the multicast session routing and VNF placement (MSVNFP) problem in NFV-SDN networks as a joint optimization problem. In this context, we propose an approach based on Genetic Algorithms (GA) called MSVNFP-GA. Given a set of multicast demands, the proposed algorithm calculates for each demand a tree and the location of VNFs seeking to minimize the total cost of links and node activation. Numerical simulations on different network topologies and traffic loads show that MSVNFP-GA is promising compared to the state-of-the-art competitive algorithms.

关键词： network function virtualization Virtual network functions Multicast Placement Genetic Algorithm

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Application Initiated Data Session as a Service for High Reliable and Safe Railway Communications 1

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6th International Conference on Advances in Computing and Data Sciences (ICACDS)

作者： Pencheva, Evelina Atanasov, Ivaylo Todor Kableshkov Univ Transport Sofia Bulgaria Tech Univ Sofia Sofia Bulgaria

ISBN: (数字)9783031126413

ISBN: (纸本)9783031126413;9783031126406

Future Railway Mobile Communication System which is critical for European Train Control Systems is expected to provide highly reliable, safe, and secure services and applications. The paper studies how mobile edge cloud computing may support the requirements of railway applications, discussing virtualization of rail functions and co-existence with mobile edge services. A new mobile edge service is designed that provides core functionality for many railways use cases enabling application-initiated and manipulated data sessions. Using the service interfaces, on-board and trackside applications can establish data sessions e.g. in case of emergency. The service is described by typical use cases, data types, resources and supported methods, and some implementation issues are discussed.

关键词： Future Railway Mobile Communication System network function virtualization Multi-Access Edge Computing Service oriented architecture

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Dependability of network Services in the Context of NFV: A Taxonomy and State of the Art Classification

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2024年第2期32卷 37-37页

作者： Azadiabad, Siamak Khendek, Ferhat Concordia Univ Dept Elect & Comp Engn Montreal PQ Canada

In the context of network function virtualization (NFV), network Services (NS) are realized by interconnecting Virtual network functions (VNF) using Virtual Links (VL). Service dependability is an important characteristic of NSs. Service dependability includes service availability, reliability, and continuity attributes. The NFV framework brings new challenges to NS dependability because of the resource-sharing possibility, NS and VNF elasticity, and the dynamicity in the NFV environment. There has been a lot of work on the dependability of NSs in the context of NFV. Existing works address different dependability attributes and use different methods and mechanisms in the proposed solutions. Thus, it is difficult to evaluate and compare these solutions, determine the well-investigated areas, and identify gaps. In this paper, we investigate the state of the art for NS dependability in the context of NFV and survey existing solutions. We define a taxonomy that represents the different aspects of NS dependability and their relations in this context. We analyze 102 papers published in the past 5 years and map them to our proposed taxonomy to understand what is addressed in the proposed solution and how. We identify the gaps and discuss potential future work directions.

关键词： network service network function virtualization Dependability Availability Reliability Continuity Taxonomy Classification State-of-the-art

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SDN-based Service Discovery and Assignment Framework to Preserve Service Availability in Telco-based Multi-Access Edge Computing 6

SDN-based Service Discovery and Assignment Framework to Pres...

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6th IEEE International Conference on Fog and Edge Computing (ICFEC)

作者： Ghorab, Amirhossein Abuibaid, Mohammed St-Hilaire, Marc Carleton Univ Ottawa ON Canada

ISBN: (纸本)9781665495240

The ever-growing number of connected User Equipment (UE), e.g., Internet of Things (IoT) devices, Connected Autonomous Vehicles (CAVs), has driven the evolution of Software-Defined networks (SDN) and Fifth-Generation (5G) networks to push the computing resources closer to the UE. Towards that end, Multi-access Edge Computing (MEC) and network function virtualization (NFV) are promising solutions to facilitate the deployment of the required user's service instances within an approximately one-hop communication range. However, discovering and assigning such service instances to the UE to maintain a high service availability is still an open challenge in the 3rd Generation Partnership Project (3GPP) standards due to the UE mobility and Telco network heterogeneity. This paper proposes an SDN-based dynamic service discovery and assignment framework for a distributed MEC infrastructure. The proposed framework considers various decision parameters such as UE's location, the service instance's demand (i.e., resource utilization), the network link status, and the service instance performance requirements (i.e., service profile) to offer a generic solution for discovering and assigning the service instances to the UE. The framework implementation results show an enhancement of the packet delivery ratio and a lower users' perceived latency.

关键词： Multi-access Edge Computing network function virtualization Service Assignment Service Discovery Software-Defined networks

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Reconfiguring network Slices at the Best Time With Deep Reinforcement Learning 11

Reconfiguring Network Slices at the Best Time With Deep Rein...

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11th IEEE International Conference on Cloud networking (CloudNet)

作者： Gausseran, Adrien Alliche, Redha A. Lesfari, Hicham Aparicio-Pardo, Ramon Giroire, Frederic Moulierac, Joanna Univ Cote Dazur CNRS Inria Sophia Antipolis Nice France

ISBN: (数字)9781665486279

ISBN: (纸本)9781665486279

The emerging 5G induces a great diversity of use cases, a multiplication of the number of connections, an increase in throughput as well as stronger constraints in terms of quality of service such as low latency and isolation of requests. To support these new constraints, network function virtualization (NFV) and Software Defined network (SDN) technologies have been coupled to introduce the network slicing paradigm. Due to the high dynamicity of the demands, it is crucial to regularly reconfigure the network slices in order to maintain an efficient provisioning of the network. A major concern is to find the best frequency to carry out these reconfigurations, as there is a trade-off between a reduced network congestion and the additional costs induced by the reconfiguration. In this paper, we tackle the problem of deciding the best moment to reconfigure by taking into account this trade-off. By coupling Deep Reinforcement Learning for decision and a Column Generation algorithm to compute the reconfiguration, we propose Deep-REC and show that choosing the best time during the day to reconfigure allows to maximize the profit of the network operator while minimizing the use of network resources and the congestion of the network. Moreover, by selecting the best moment to reconfigure, our approach allows to decrease the number of needed reconfigurations compared to an algorithm doing periodic reconfigurations during the day.

关键词： Deep learning Costs network slicing Reinforcement learning Quality of service Throughput network function virtualization

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Optimizing Virtual network function Splitting in Open-RAN Environments 47

Optimizing Virtual Network Function Splitting in Open-RAN En...

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47th IEEE Conference on Local Computer networks (LCN)

作者： Amiri, Esmaeil Wang, Ning Shojafar, Mohammad Tafazolli, Rahim Inst Commun Syst ICS 5GIC & 6GIC Guildford England

ISBN: (数字)9781665480017

ISBN: (纸本)9781665480017

Open radio access network (Open-RAN) is becoming a key component of cellular networks, and therefore optimizing its architecture is vital. The Open-RAN is a distributed architecture that lets the virtualized networking functions be split between Distributed Units (DU) and Centralized Units (CUs);as a result, there is a wide range of design options. We propose an optimization problem to choose the split points. The objective is to balance the load across CUs as well as midhaul links by considering delay requirements. The resulting formulation is an NP-hard problem that is solved with a novel heuristic algorithm. Performance evaluation shows that the gap between optimal and heuristic solutions does not exceed 2%. An in-depth analysis of different centralization levels shows that using multi-CUs could reduce the total bandwidth usage by up to 20%. Moreover, multipath routing can improve the result of load balancing between midhaul links while increasing bandwidth usage.

关键词： Open Radio Access network (Open-RAN) network function virtualization network Optimization

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Dynamic network Slicing and Resource Allocation for 5G-and-Beyond networks

Dynamic Network Slicing and Resource Allocation for 5G-and-B...

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IEEE Wireless Communications and networking Conference (IEEE WCNC)

作者： Abdellatif, Alaa Awad Mohamed, Amr Erbad, Aiman Guizani, Mohsen Qatar Univ Coll Engn Doha Qatar Hamad Bin Khalifa Univ Coll Sci & Engn Ar Rayyan Qatar Mohamed Bin Zayed Univ Artificial Intelligence Machine Learning Dept Abu Dhabi U Arab Emirates

ISBN: (纸本)9781665442664

5G networks are designed not only to transport data, but also to process them while supporting a vast number of services with different key Performance Indicators (KPIs). network virtualization has emerged to enable this vision, however it calls for designing efficient computing and network resource allocation schemes to support diverse services, while jointly considering all KPIs associated with these services. Thus, this paper proposes a dynamic network slicing and resource allocation framework that aims at maintaining high-level network operational performance, while fulfilling diverse services' requirements and KPIs, e.g., availability, reliability, and data quality. Differently from the existing works, which are designed considering traditional metrics like throughput and latency, we present a novel methodology and resource allocation schemes that enable high-quality selection of radio points of access, resource allocation, and data routing from end users to the cloud. Our results depict that the proposed solutions could obtain the best trade-off between diverse services' requirements when compared to baseline approaches that consider partial network view or fair resource allocation.

关键词： 5G networks network function virtualization Software-defined networking RAN slicing

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Post-fault restoration of service function chains in fog networks

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COMPUTER networkS 2024年 251卷

作者： Siasi, N. Jasim, M. A. Ghani, N. DePaul Univ Sch Comp Chicago IL 60604 USA Univ Washington Sch Engn & Technol Tacoma WA 98402 USA Univ S Florida Dept Elect Engn Tampa FL 33620 USA

The network function virtualization (NFV) paradigm is rapidly being adopted by enterprises and service providers as an alternative to proprietary hardware. It enables virtual network functions (VNFs) to be embedded on commercial edge servers for the delivery of highly-specialized service function chains (SFCs). Here embedding SFC requests on fog computing supports clients with stringent delay requirements and contextual service requirements. Now one of the major challenges is the survivability of embedded service chains in fog computing, which may be compromised due to node, link, and application failures. These failures can disrupt service continuity and degrade the quality-of-service. Therefore, there is a demand for SFC provisioning to be more resilient, incorporating rapid restoration techniques that oppose proactive solutions that reserve backup paths, subsequently compromising network capacity. Hence, this paper presents heuristic methods for post-fault SFC restorations due to multiple failures in fog computing. These methods establish post-provisioning restoration for failed requests, known as end-to-end (E2E) and intermediate (IM) restoration, that aim to restore paths with the least delay and cost.

关键词： network function virtualization Service function chaining Fog computing Survivability Restoration

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Distributed service function chaining in NFV-enabled networks: A game-theoretic learning approach

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JOURNAL OF COMPUTATIONAL SCIENCE 2024年 82卷

作者： Alikhani, Mahsa Hakami, Vesal Sheikhi, Marzieh Iran Univ Sci & Technol Sch Comp Engn Tehran Iran Iran Univ Sci & Technol Ctr Excellence Future Networks Sch Comp Engn Tehran *** Iran

In network function virtualization (NFV), Service function Chaining (SFC) provides an ordered sequence of virtual network functions (VNFs) and subsequent steering of traffic flows through them to cater to end-to-end services. This paper addresses the NP-hard problem of minimum cost SFC deployment to support customer services that access the carrier network's NFV infrastructure (NFVI) through some edge routers. To determine the mappings of VNFs to physical servers, a challenging aspect would be the inter-server latencies that may fluctuate over time because of the sharing nature of cloud data centers. To construct the SFC, we come up with three different formulations, each corresponding to a different informational assumption about the link latencies: First, a centralized integer linear programming (ILP) formulation is given under the assumption of the non-causal availability of exact and instantaneous inter-server latencies. The solution to this ILP can serve as a lower bound to benchmark more scalable and realistic schemes. Next, we give a distributed game-theoretic formulation (with service broker agents as players) which only requires the statistical knowledge of link latency fluctuations. The game provably admits a pure Nash equilibrium (NE) and can be solved iteratively through the well-known best response dynamics (BRD) algorithm. Our main novelty lies in the third formulation in which each service broker has neither instantaneous nor statistical knowledge of the latencies. Instead, it relies on a game-theoretic learning algorithm to compose its VNF chain only based on its own history of adopted decisions and experienced delays on each logical link. We prove that the proposed learning algorithm asymptotically converges to NE and evaluate its performance through simulations in terms of convergence and the impact of network parameters.

关键词： Service function Chaining network function virtualization VNF Game-Theoretic Learning

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An Efficient Service function Chains Orchestration Algorithm for Mobile Edge Computing

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KSII TRANSACTIONS ON INTERNET AND INFORMATION SYSTEMS 2021年第12期15卷 4364-4384页

作者： Wang, Xiulei Xu, Bo Jin, Fenglin Peoples Liberat Army Engn Univ Inst Command & Control Engn Nanjing 210007 Peoples R China

The dynamic network state and the mobility of the terminals make the service function chain (SFC) orchestration mechanisms based on static and deterministic assumptions hard to be applied in SDN/NFV mobile edge computing networks. Designing dynamic and online SFC orchestration mechanism can greatly improve the execution efficiency of compute-intensive and resource-hungry applications in mobile edge computing networks. In order to increase the overall profit of service provider and reduce the resource cost, the system running time is divided into a sequence of time slots and a dynamic orchestration scheme based on an improved column generation algorithm is proposed in each slot. Firstly, the SFC dynamic orchestration problem is formulated as an integer linear programming (ILP) model based on layered graph. Then, in order to reduce the computation costs, a column generation model is used to simplify the ILP model. Finally, a two-stage heuristic algorithm based on greedy strategy is proposed. Four metrics are defined and the performance of the proposed algorithm is evaluated based on simulation. The results show that our proposal significantly provides more than 30% reduction of run time and about 12% improvement in service deployment success ratio compared to the Viterbi algorithm based mechanism.

关键词： Mobile Edge Computing Internet of Things Service function Chain Column Column Generation network function virtualization

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