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IFIP/IEEE International Symposium on Integrated network Management (IM)

作者： Lopes, Filipe B. Nazar, Gabriel Luca Schaeffer-Filho, Alberto E. Univ Fed Rio Grande do Sul Inst Informat Porto Alegre RS Brazil

ISBN: (纸本)9783903176324

The expected benefits of network function virtualization (NFV), i.e., flexibility and efficiency, require platforms able to instantiate Virtualized network functions (VNFs), replacing traditional dedicated middleboxes. However, to fulfill performance requirements, especially for functions operating at high-throughput line rates, dedicated hardware acceleration may be required and, to provide the expected flexibility, hardware accelerators must be able to support different VNFs. Thus, reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) have received attention due to their ability to provide both properties. Not all VNFs, however, require or are even suitable for hardware acceleration and, therefore, heterogeneous platforms composed of FPGAs and General Purpose Processors (GPPs) can be used. Even for a single network function, distinct VNF Components (VNFCs) may have different demands and restrictions, meaning that different hardware substrates may be more suitable for their implementation. In this paper, with the goal of promoting the efficient and seamless integration of accelerators in NFV, we propose VNFAccel, a platform to manage the execution of VNFCs in a heterogeneous infrastructure. We evaluate the effectiveness of FPGAs as accelerator devices for two VNF case studies and analyze the instantiation latency of FPGA-based VNFCs in the platform. We also provide guidelines to design VNFCs that are more flexible, promoting increased reuse and reducing configuration time, and identify properties that make them suitable for FPGA implementation.

关键词： FPGA network function virtualization hardware acceleration

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Incentive-Stable Matching Protocol for Service Chain Placement in Multi-Operator Edge System 22

Incentive-Stable Matching Protocol for Service Chain Placeme...

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22nd Asia-Pacific network Operations and Management Symposium (APNOMS)

作者： Wang, Jen-Yu Yen, Li-Hsing Liman, Juliana Natl Yang Ming Chiao Tung Univ Dept Comp Sci Hsinchu Taiwan

ISBN: (纸本)9784885523328

network function virtualization (NFV) enables the embedding of Virtualized network function (VNF) into commodity servers. A sequence of VNFs can be chained in a particular order to form a service chain (SC). This paper considers placing multiple SCs in a geo-distributed edge system owned by multiple service providers (SPs). For a pair of SC and SP, minimizing the placement cost while meeting a latency constraint is formulated as an integer programming problem. As SC clients and SPs are self-interested, we study the matching between SCs and SPs that respects individual's interests yet maximizes social welfare. The proposed matching approach excludes any blocking individual and block pair which may jeopardize the stability of the result. Simulation results show that the proposed approach performs well in terms of social welfare but is suboptimal concerning the number of placed SCs.

关键词： Integer programming Data centers Cloud computing Protocols Simulation Stability analysis network function virtualization

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Energy-Efficient VNF Deployment for Graph-Structured SFC Based on Graph Neural network and Constrained Deep Reinforcement Learning 22

Energy-Efficient VNF Deployment for Graph-Structured SFC Bas...

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22nd Asia-Pacific network Operations and Management Symposium (APNOMS)

作者： Qi, Siyu Li, Shuopeng Lin, Shaofu Saidi, Mohand Yazid Chen, Ken Beijing Univ Technol Fac Informat Technol Beijing Peoples R China Univ Sorbonne Paris Nord Inst Galilee L2TI Villetaneuse France

ISBN: (纸本)9784885523328

network function virtualization (NFV), which decouples network functions from hardware and transforms them into hardware-independent Virtual network functions (VNF), is a crucial technology for many emerging networking domains, such as 5G, edge computing and data-center network. Service function Chaining (SFC) is the ordered set of VNFs. The VNF deployment problem is to find the optimal deployment strategy of VNFs in SFC while guaranteeing the Service-Level Agreements (SLAB). Existing VNF deployment researches mainly focus on sequences of VNFs without energy consideration. However, with the rapid development of application requirement, the SFCs evolve from sequence to dynamic graph and the service providers become more and more sensitive to the energy consumption in NFV. Therefore, in this paper, we identify the Energy-efficient Graph-structured SFC problem (EG-SFC) and formulate it as a Combinatorial Optimization Problem (COP). Benefiting from the recent advances in machine learning for COP, we propose an end-toend Graph Neural network (GNN) based on constrained Deep Reinforcement Learning (DRL) method to solve EG-SFC. Our method leverages the Graph Convolutional network (GCN) to represent the Q-network of Double Deep Q-network (DDQN) in DRL. The mask mechanism is proposed to deal with the resources constraints in COP. The experimental results show that the proposed method can deal with unseen SFC graphs and achieve better performances than greedy algorithm and traditional DDQN.

关键词： network function virtualization Service function Chaining Virtual network function Graph Neural network Deep Reinforcement Learning

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Cost-Efficient Dynamic Service function Chain Embedding in Edge Clouds 17

Cost-Efficient Dynamic Service Function Chain Embedding in E...

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17th International Conference on network and Service Management (CNSM) - Smart Management for Future networks and Services

作者： Chen, Weihan Wang, Zhiliang Zhang, Han Yin, Xia Shi, Xingang Tsinghua Univ Beijing Peoples R China

ISBN: (纸本)9783903176362

Edge Computing (EC) provides delay protection for some delay-sensitive network services by deploying cloud infrastructure with limited resources at the edge of the network. In addition, network function virtualization (NFV) implements network functions by replacing traditional dedicated hardware devices with Virtual network function (VNF) that can run on general servers. In NFV environment, Service function Chaining (SFC) is regarded as a promising way to reduce the cost of configuring network services. NFV therefore allows to deploy network functions in a more flexible and cost-efficient manner, and schedule network resources according to the dynamical variation of network traffic in EC. For service providers, seeking an optimal SFC embedding scheme can improve service performance and reduce embedding cost. In this paper, we study the problem of how to dynamically embed SFC in geo-distributed edge clouds network to serve user requests with different delay requirements, and formulate this problem as a Mixed Integer Linear Programming (MILP) which aims to minimize the total embedding cost. Furthermore, a novel SFC Cost-Efficient emBedding (SFC-CEB) algorithm has been proposed to efficiently embed required SFC and optimize the embedding cost. Based on the results of trace-driven simulations, the proposed algorithm can reduce SFC embedding cost by up to 37% compared with state-of-the-art schemes (e.g., RDIP).

关键词： network function virtualization Edge Computing Service function Chaining traffic routing

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An Efficient Algorithm for Service function Chains Reconfiguration in Mobile Edge Cloud networks

An Efficient Algorithm for Service Function Chains Reconfigu...

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IEEE International Conference on Web Services (ICWS) / IEEE World Congress on Services (IEEE SERVICES)

作者： Li, Biyi Cheng, Bo Chen, Junliang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Peoples R China

ISBN: (纸本)9781665416818

Mobile Edge Computing (MEC) supports ultra-low latency and high-bandwidth services as an emerging network architecture by deploying servers at the edge of the network to provide computing and storage resources. Along with the MEC technology, network function virtualization (NFV) provisions Service function Chains (SFC) on MEC servers to improve user service experience and achieve fast access to the mobile user. However, users are constantly moving in the edge network, and different users usually have different delay requirements for service requests. To guarantee the QoS of mobile users, it is necessary to migrate SFCs to an advisable edge server when users move across Base Stations (BS). This paper focuses on the SFCs reconfiguration scheme with resource capacity constraints in the MEC network to support the seamless migration of mobile user services. We first formalize the SFCs reconfiguration problem of the edge network as a mathematical model, which aims to minimize the end-to-end delay and operating costs of user services. Then, we convert the problem into an equivalent shortest path problem and design a Dynamic Programmingbased SFC Migration algorithm (DPSM). Finally, we conduct simulation experiments to evaluate the performance of the algorithm based on a real-world dataset. The experiment results show the effectiveness and efficiency of our algorithm.

关键词： Mobile edge computing network function virtualization service function chain seamless migration user mobility

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Memory network Architecture for Packet Processing in functions virtualization 7

Memory Network Architecture for Packet Processing in Functio...

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IEEE 7th International Conference on network Softwarization (NetSoft) - Accelerating network Softwarization in the Cognitive Age

作者： Korikawa, Tomohiro Oki, Eiji Kyoto Univ Grad Sch Informat Kyoto Japan

ISBN: (纸本)9781665405225

Packet processing tasks in network functions issue memory requests to understand the packet information, update the packet content, and search the databases, which requires high-performance memory systems. While network functions virtualization (NFV) is expected to reduce the cost of network infrastructure by replacing dedicated network equipment with commercial off-the-shelf (COTS) hardware and virtual network functions (VNFs), VNF performance suffers from the poor memory systems that lack function-dedicated memories and memory parallelism in COTS servers. While several works presented parallel memories for packet processing based on 3 dimensional (3D)-stacked dynamic random access memories (DRAMs), data transfer latency between the processors and memories are not considered. Although there are processing-in-memory (PIM) architectures that offload a part of processing in memories to reduce data transfers, the majority of processing is still in the processors, which requires data transfers for multiple packet processing tasks. This paper proposes a memory network architecture using 3D-stacked DRAMs to increase throughput and reduce accumulated latency when there are multiple packet processing tasks. Packets that enter the memory network receive packet processing at each 3D-stacked DRAM without data transfers between the processors and memories. The evaluation results show that the proposed architecture increases throughput and reduces accumulated latency for memory accesses and data transfers when there are multiple packet processing tasks, compared to the conventional architecture with 3D-stacked DRAMbased parallel memory, where every memory access requires data transfers.

关键词： Program processors Memory management Random access memory Telecommunication traffic Data transfer Throughput network function virtualization

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Optimizing NFV deployment in Segment Routing 16

Optimizing NFV deployment in Segment Routing

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16th Iberian Conference on Information Systems and Technologies (CISTI)

作者： Camaz, Goncalo Pereira, Vitor Rocha, Miguel Sousa, Pedro Univ Minho Dept Informat Braga Portugal Univ Minho Dept Informat Ctr Engn Biol Braga Portugal Univ Minho Dept Informat Ctr Algoritmi Braga Portugal

ISBN: (纸本)9789895465910

Segment Routing (SR) is an implementation of Software-Defined networking (SDN) for traffic routing. It derives from a source routing paradigm where each node, at the network's periphery, adds a list of labels to the packet's header defining explicitly the path each traffic flow should follow to its destination. Each label is a segment that identifies a topological instruction, a service, or even a processing instruction. Although SR can be very similar to Multi-Protocol Label Switching (MPLS), concerning the simple routing of packets, its utilization simplifies the network management tasks. On the other hand, SR provides solutions to existing scalability problems on SDN implementations, for example, OpenFlow-based. This technology is rapidly becoming a standard and is already supported by big players such as Cisco and Huawei, performing a fundamental role in the architecture of future 5G networks. Also, due to these new technology capabilities, there is an increasing number of novel services. This growth, allied with the rise of 5G capable devices, motivated the deployment of services on crucial points of the network. Consequently, mobile operators created the network function virtualization (NFV) concept. However, some important questions should be considered, such as how to optimize network resources regarding service locations to reduce the congestion level on the network. The main contribution of this work consists of exploring solutions based on SR and NFV. Thus, relying on optimization techniques to pursue optimal resource allocation for traffic routing and service processing requirements.

关键词： Evolutionary Algorithms Optimization network function virtualization Segment Routing

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Intelligent network Service Embedding using Genetic Algorithms 26

Intelligent Network Service Embedding using Genetic Algorith...

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26th IEEE Symposium on Computers and Communications (IEEE ISCC)

作者： Rodis, Panteleimon Papadimitriou, Panagiotis Univ Macedonia Thessaloniki Greece

ISBN: (纸本)9781665427449

network function virtualization (NFV) opens us great opportunities for network processing with higher resource efficiency and flexibility. Nevertheless, intelligent orchestration mechanisms are required, such that NFV can exploit its potential and fill up to its promise. In this respect, we investigate the potential gains of embracing Artificial Intelligence (AI) for the virtual network function (VNF) placement problem. To this end, we design and evaluate a genetic algorithm, which seeks efficient embeddings with runtimes on par with heuristic methods. Our proposed embedding method exhibits innovations in terms of network representation and algorithm design, thereby, deviating from typical genetic algorithms. Compared to a heuristic, the proposed genetic algorithm yields higher request acceptance rates, stemming from more efficient resource utilization. We further study a range of factors and parameters that affect the efficiency of the genetic algorithm.

关键词： Technological innovation Intelligent networks Runtime Simulation Reinforcement learning network function virtualization Resource management

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CloudSimSFC: Simulating Service function chains in Multi-Domain Service networks

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SIMULATION MODELLING PRACTICE AND THEORY 2022年第0期120卷

作者： Sun, Jie Wo, Tianyu Liu, Xudong Cheng, Rui Mou, Xudong Guo, Xiaohui Cai, Haibin Buyya, Rajkumar Beihang Univ Sch Comp Sci & Engn SKLSDE Beijing Peoples R China Beihang Univ Sch Software SKLSDE Beijing Peoples R China Pinduoduo Corp Shanghai Peoples R China Beihang Univ Res Ctr Big Data & Computat Intelligence Hangzhou Inst Hangzhou Peoples R China East China Normal Univ Software Engn Inst Shanghai Peoples R China Univ Melbourne Sch Comp & Informat Syst Cloud Comp & Distributed Syst CLOUDS Lab Melbourne Australia

Service function Chain (SFC) is widely adopted in Multi-domain Service networks (MDSN) to enforce network policies on customer traffic. Great effort has been devoted to the research of SFC deployment strategies. In this context, simulators are helpful to the design and evaluation of those strategies. A good SFC simulator should be accurate, comprehensive and user-friendly for SFC simulation. However, existing simulators fail to satisfy the requirement due to two major drawbacks: First, they overlook the resource heterogeneity and performance instability of the MDSN environment. Second, their performance models for service functions are too simple to contain the important features such as traffic changing effect and packet queue. To overcome these drawbacks, we propose CloudSimSFC - a new SFC simulator that (1) simulates the performance fluctuations and server failure/recovery events in MDSN environment to align with the performance instability of real-world systems, (2) elaborates the modeling of service functions by incorporating the computation components such as CPU and queue, and the traffic changing effect which happens during packet processing, (3) employs scenario abstraction to simplify the definition of new (heterogeneous) simulation scenarios and supports standard service metrics like request-response time. With these features, CloudSimSFC can be used to simulate SFC run-time performance and evaluate deployment strategies. We introduce the system architecture of CloudSimSFC to explain the simulation principle. We conduct extensive experiments to evaluate the simulation accuracy of CloudSimSFC by comparing it with an SFC prototype. Experimental results confirm that CloudSimSFC achieves 95%+ accuracy in all the evaluation scenarios. We also evaluate the simulation running time and analyze the overhead caused by the proposed simulation features. Finally, we demonstrate the primary usage of CloudSimSFC with case studies.

关键词： Multi-domain service network Service function chain Deployment strategy Simulation network function virtualization

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A Scalable Hierarchically Distributed Architecture for Next-Generation Applications

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JOURNAL OF network AND SYSTEMS MANAGEMENT 2022年第1期30卷 1-1页

作者： Ravuri, Hemanth Kumar Vega, Maria Torres van der Hooft, Jeroen Wauters, Tim De Turck, Filip Univ Ghent IMEC IDLab Ghent Belgium

The rigidity of traditional network architectures, with tightly coupled control and data planes, impairs their ability to adapt to highly dynamic requirements of future application domains. While Software-Defined networking (SDN) can provide the required dynamism, it suffers from scalability issues. Therefore, efforts have been made to propose alternative decentralized solutions, such as the flat distributed SDN architecture. Such alternatives address the scalability problem for mainly local flows, but are impaired by a substantial increase in the overhead for cross-domain flow setup. To manage the trade-off between scalability and overhead, there is a need for intermediate hierarchical solutions. However, these have not been explored to the complete potential so far. Furthermore, the network function virtualization (NFV) paradigm complements SDN by offering computational and storage services in the form of Virtual network functions (VNFs). When integrated seamlessly, both SDN and NFV can offer solutions to the problems posed by highly dynamic application domains. Hence, this work proposes a scalable hierarchical SDN control plane architecture for SDN/NFV-based next-generation application domains such as immersive media delivery system. We have implemented the proposed architecture based on the well-known state-of-the-art ZeroSDN controller. To evaluate the performance of the architecture, we have implemented an on-demand immersive media (point cloud) streaming application and varied the load on the control plane using the background traffic. To benchmark our solution, we have evaluated its performance in comparison with the centralized and flat distributed architectures. We show that the proposed architecture performs better than the rest in terms of scalability, lost flows, and processing latency. Our study shows that the proposed architecture when distributed to three controllers, accepts 23% more flows with almost 70% reduced processing latency compared to the s

关键词： Controller network function virtualization Scalability Software-Defined networking

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