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DEFT: Distributed, Elastic, and Fault-tolerant State Management of network functions 19

DEFT: Distributed, Elastic, and Fault-tolerant State Managem...

19th International Conference on network and Service Management (CNSM) - network and Service Management in the Era of Generative AI and Digital Twins

作者： Shahriyar, Md Mahir Saha, Gourab Bhattacharjee, Bishwajit Reaz, Rezwana Bangladesh Univ Engn & Technol Dept Comp Sci & Engn Dhaka Bangladesh

ISBN: (纸本)9783903176591

network function virtualization is the key to developing elastically scalable and fault-tolerant network functions (e.g. load balancer, firewall etc.). By integrating NFV and SDN technologies, it is feasible to dynamically reroute traffic to new network function (NF) instances in the event of an NF failure or overload scenario. The fact that the majority of network functions are stateful makes the task more challenging. State migration and state replication are common approaches in achieving elasticity and fault tolerance. The majority of the studies in the literature either emphasize fault tolerance or elastic scalability while designing a state management system for network functions. In this paper, we have designed a complete state management system, called DEFT, that meets both elasticity and fault-tolerance goals. Our system also supports strong consistency on global state updates. While existing designs rely on a central controller or remote central storage to achieve strong consistency on state updates, DEFT utilizes distributed consensus mechanism to achieve the same. We have done a proof of concept implementation of DEFT and extensively tested DEFT under several model conditions to evaluate its scalability and performance. Our experimental results show that DEFT is scalable and maintains a considerably high throughput throughout. It incurs minimal performance overhead while achieving strong consistency on state updates.

关键词： network function virtualization Software defined networking Distributed computing Fault tolerant systems

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HARS: A High-Available and Resource-Saving Service function Chain Placement Approach in Data Center networks

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2022年第2期19卷 829-847页

作者： Niu, Meng Han, Qingmian Cheng, Bo Wang, Meng Xu, Ziqi Gu, Wenyuan Zhang, Shuhao Chen, Junliang Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100000 Peoples R China China Elect Technol Grp Corp Res Inst 54 Shijiazhuang 050002 Hebei Peoples R China

network function virtualization (NFV) is a promising technology that decouples network functions from hardware. Connecting virtual network functions (VNFs) in series to form a service function chain (SFC) can flexibly orchestrate and expand network functions. However, there are higher availability requirements for SFCs. This paper aims to solve the SFC placement problem under availability and resource constraints. This paper proposes the sideway cross (SC) backup model, which considers the availability of both VNFs and physical machines (PMs) in a data center. The SC model cross-arranges the backup instances of VNFs to guarantee availability and optimize resource consumption. Then, this paper proposes the heuristic meteor shower optimization (MSO) algorithm to place SFCs. Compared to traditional heuristic algorithms, MSO can improve the execution time by approximately 200%. Combined with the SC backup model, MSO can effectively improve the availability and resource overhead. The evaluation results show that the proposed approach can guarantee higher availability and consumes fewer resources. The proposed approach only needs 75% of the resources to achieve the same availability as the state-of-the-art models.

关键词： Switches Heuristic algorithms Data centers Costs Servers Reliability Approximation algorithms network function virtualization service function chain availability backup resources allocation

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Mobility-Aware and Delay-Sensitive Service Provisioning in Mobile Edge-Cloud networks

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2022年第1期21卷 196-210页

作者： Ma, Yu Liang, Weifa Li, Jing Jia, Xiaohua Guo, Song Australian Natl Univ Res Sch Comp Sci Canberra ACT 2601 Australia City Univ Hong Kong Dept Comp Sci Kowloon 83 Tat Chee Ave Hong Kong Peoples R China Hong Kong Polytech Univ Hong Kong Peoples R China

Mobile edge computing (MEC) has emerged as a promising technology to push the cloud frontier to the network edge, provisioning network services in proximity of mobile users. Serving users at edge clouds can reduce service latency, lower operational cost, and improve network resource availability. Along with the MEC technology, network function virtualization (NFV) is another promising technique that implements various network service functions as pieces of software in cloudlets (servers or clusters of servers). Providing virtualized network service for mobile users can improve user service experience, simplify network service deployment, and ease network resource management. However, mobile users move in networks arbitrarily, and different users usually request different services with different resource demands and delay requirements. It thus poses a great challenge to providing reliable and seamless virtualized network services for mobile users in an MEC network while meeting their individual delay requirements, subject to resource capacities on the network. In this paper, we focus on the provisioning of virtualized network function services for mobile users in MEC that takes into account user mobility and service delay requirements. We first formulate two novel optimization problems of user service request admissions with the aims to maximize the accumulative network utility and accumulative network throughput for a given time horizon, respectively. We then devise a constant approximation algorithm for the utility maximization problem. We also develop an online algorithm for the accumulative throughput maximization problem. We finally evaluate the performance of the proposed algorithms through experimental simulations. Experimental results demonstrate that the proposed algorithms are promising.

关键词： Cloud computing Approximation algorithms Delays Mobile computing Mobile handsets Prediction algorithms Servers Mobile Edge computing network function virtualization VNF instance deployment virtualized service provisioning approximation and online algorithms delay-sensitive request admission utility gain maximization user mobility cloudlets or edge-clouds resource allocations and provisioning in MEC optimization problems

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ScaleFlux: Efficient Stateful Scaling in NFV

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2022年第12期33卷 4801-4817页

作者： Liu, Libin Xu, Hong Niu, Zhixiong Li, Jingzong Zhang, Wei Wang, Peng Li, Jiamin Xue, Jason Chun Wang, Cong Zhongguancun Lab Beijing 100190 Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Hong Kong Peoples R China Microsoft Res Asia Beijing 100080 Peoples R China City Univ Hong Kong Dept Comp Sci Hong Kong Peoples R China Qilu Univ Technol Shandong Comp Sci Ctr Shandong Prov Key Lab Comp Networks NationalSupercomp Ctr JinanShandong Acad Sci Jinan 250316 Shandong Peoples R China Huawei Hong Kong Res Ctr Theory Lab Hong Kong Peoples R China

network function virtualization (NFV) enables elastic scaling to middlebox deployment and management. Therefore, efficient stateful scaling is an important task because operators often need to shift traffic and the associated flow states across VNF instances to deal with time-varying loads. Existing NFV scaling methods, however, typically focus on one aspect of the scaling pipeline and does not offer an end-to-end scaling framework. This article presents ScaleFlux, a complete stateful scaling system that efficiently reduces flow-level latency and achieves near-optimal resource usage. ScaleFlux (1) monitors traffic load for each VNF instance and adopts a queue-based mechanism to detect load burstiness timely, (2) deploys a flow bandwidth predictor to predict flow bandwidth time-series with the ABCNN-LSTM model, and (3) schedules the necessary flow and state migration using the simulated annealing algorithm to achieve both flow-level latency guarantee and resource usage minimization. Testbed evaluation with a five-machine cluster shows that ScaleFlux reduces flow completion time by at least 8.7x for all the workloads and achieves near-optimal CPU usage during scaling.

关键词： Logic gates Bandwidth Service level agreements Packet loss Computer science Cloud computing Wide area networks network function virtualization network load detection flow bandwidth prediction stateful scaling service level agreements

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Dynamic Service Chain Construction Based on Model Predictive Control in NFV Environments

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IEICE TRANSACTIONS ON COMMUNICATIONS 2022年第4期E105B卷 399-410页

作者： Kumazaki, Masaya Ogura, Masaki Tachibana, Takuji Univ Fukui Grad Sch Engn Fukui 9108507 Japan Osaka Univ Grad Sch Informat Sci & Technol Osaka Japan

For beyond 5G era, in network function virtualization (NFV) environments, service chaining can be utilized to provide the flexible network infrastructures needed to support the creation of various application services. In this paper, we propose a dynamic service chain construction based on model predictive control (MPC) to utilize network resources. In the proposed method, the number of data packets in the buffer at each node is modeled as a dynamical system for MPC. Then, we formulate an optimization problem with the predicted amount of traffic injecting into each service chain from users for the dynamical system. In the optimization problem, the transmission route of each service chain, the node where each VNF is placed, and the amount of resources for each VNF are determined simultaneously by using MPC so that the amount of resources allocated to VNFs and the number of VNF migrations are minimized In addition, the performance of data transmission is also controlled by considering the maximum amount of data packets stored in buffers. The performance of the proposed method is evaluated by simulation, and the effectiveness of the proposed method with different parameter values is investigated.

关键词： network function virtualization service chaining VNF model predictive control optimization problem

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ECF-YOLOv7-Tiny: Improving Feature Fusion and the Receptive Field for Lightweight Object Detectors

ECF-YOLOv7-Tiny: Improving Feature Fusion and the Receptive ...

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2025 IEEE/CVF Winter Conference on Applications of Computer Vision, WACV 2025

作者： Bacea, Dan-Sebastian Oniga, Florin Technical University of Cluj-Napoca Romania Stratec Biomedical Romania

ISBN: (纸本)9798331510831

In this work, we aim to increase the efficiency and the detection performance of lightweight object detectors, with focus on feature fusion and receptive field of the models. For improved feature fusion, we introduce the Convolutional Squeeze-and-Excitation (CSE) module, which requires only minimal additional computation. For improving the receptive field and feature extraction capabilities in a resource effective manner, we introduce the Cross-Stage Partial Context Augmentation Module (CSP-CAM). Furthermore, for improving real-time performance, we apply two model scaling techniques with minimal impact on the detection performance. We prove the effectiveness of the proposed modules by inserting them into YOLOv7-tiny and YOLOv9-t. We build a new network architecture, ECF-YOLOv7-tiny, which we train on the MS COCO dataset and evaluate the inference speed on NVIDIA Jetson Nano. ECF-YOLOv7-tiny achieves 37.8% mAP @ [0.5:0.95] on the test set while reaching 9.3 FPS on Jetson Nano, outperforming the other state-of-the-art lightweight object detectors on the 416 input image resolution. Code and models are released at: https://***/dbacea/ecf-yolov7-tiny. © 2025 IEEE.

关键词： network function virtualization

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Multi-Constrained Routing-Based Heuristic for VNF Placement and Chaining

Multi-Constrained Routing-Based Heuristic for VNF Placement ...

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IEEE International Conference on Communications (IEEE ICC)

作者： Ikhelef, Issam Abdeldjalil Saidi, Mohand Yazid Li, Shuopeng Chen, Ken Univ Sorbonne Paris Nord Inst Galilee L2TI F-93430 Villetaneuse France Beijing Univ Technol Fac Informat Technol Beijing Peoples R China

ISBN: (纸本)9781538674628

network softwarization makes it easy to quickly deploy various and different network services with the composition of virtual network functions (VNFs) that can be launched, modified and stopped at any time. Nowadays, several VNF servers supporting different types of VNFs exist. Therefore, to minimize the cost of deploying network services, VNFs should not only be placed on the best servers but also chained in an optimal way. In this paper, we propose a new approach to solve the NP-hard VNF placement and chaining problem (VNFPC problem). After proving that VNFPC problem can be transformed to a variant of the multi-constrained routing problem where the number of additive metrics is part of the problem, we proposed efficient heuristic reducing the worst-case time complexity while ensuring high quality solutions. Simulation results show that our constrained shortest paths-based heuristics allows to determine solutions close to the optima by keeping small number of paths on nodes.

关键词： Virtual network function network function virtualization Service function Chain Optimization Multi-constrained Routing Heuristic

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Online Virtual network function Scheduling Towards Deterministic Latency

Online Virtual Network Function Scheduling Towards Determini...

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IEEE Conference on Global Communications (IEEE GLOBECOM) - Intelligent Communications for Shared Prosperity

作者： Kuai, Zhenran Wang, Shaowei Nanjing Univ rch Elect Sci & Engn Nanjing 210023 Peoples R China

ISBN: (纸本)9798350310900

network function virtualization aims to deploy virtual network functions (VNFs) on commercial off-the-shelf hardware, allowing for efficient implementation of network services by scheduling various VNFs. However, the requirements of deterministic networking poses higher demands on VNF scheduling to achieve guaranteed latency performance. In this paper, we study the online VNF scheduling problem with the objective of minimizing the system cost regarding to unfinished services while improving the determinism of latency. The formulated optimization task yields a mixed integer program problem and we propose an online VNF scheduling algorithm to tackle it, which transforms the end-to-end latency constraint into deadlines for each VNF and adopts an online primal-dual method to generate scheduling decisions. Numerical results show that the proposed scheduling algorithm outperforms two traditional rule-based scheduling methods in terms of latency and acceptance ratio.

关键词： Deterministic networking network function virtualization online scheduling service function chain

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Virtual network function Migration Considering Load Balance and SFC Delay in Cloud Datacenter 16

Virtual Network Function Migration Considering Load Balance ...

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IEEE 16th International Conference on Cloud Computing (IEEE CLOUD)

作者： Yue, Yi Tang, Xiongyan Yang, Wencong Zhang, Zhiyan Zhang, Xuebei China Unicom Res Inst Future Network Res Dept Beijing Peoples R China

ISBN: (纸本)9798350304817

With the emergence of network function virtualization (NFV) and Software-Defined networks (SDN), Service function Chaining (SFC) has evolved into a popular paradigm for carrying and fulfilling network services. This new networking and computing paradigm enables virtual network functions (VNFs) to be placed in virtual machines/software entities on a network of physical devices elastically and flexibly with lower capital and operating expenditures. However, for cloud service providers, how to migrate VNFs in NFV-enabled networks for more flexible services is a critical issue that needs to be addressed. Currently, research on VNF migration mainly focuses on how to migrate a single VNF while ignoring the VNF sharing and concurrent migration. This paper assumes that each placed VNF can serve multiple SFCs. We focus on selecting the best migration location for concurrently migrating VNF instances based on actual network conditions. First, we formulate the VNF migration problem as an optimization model whose goal is to minimize the end-to-end delay of all influenced SFCs while guaranteeing network load balance after migration. Next, we design a Two-Stage Hybrid Genetic Evolution (T-SHGE) solution to solve the VNF migration problem. Finally, we combine previous experimental data to generate realistic VNF traffic patterns and evaluate the algorithm. Simulation results show that the SFC delay after migration calculated by T-SHGE is close to the optimal results and much lower than the benchmarks. In addition, it effectively guarantees the load balancing of the network after migration.

关键词： network function virtualization Service function chain QoS guarantee

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Control Groups Added Latency in NFVs: An Update Needed?

Control Groups Added Latency in NFVs: An Update Needed?

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4th IEEE Conference on network function virtualization / 9th Software Defined networks Conference (IEEE NFV-SDN)

作者： Wiedner, Florian Daichendt, Alexander Andre, Jonas Carle, Georg Tech Univ Munich Chair Network Architectures & Serv Sch Computat Informat & Technol Munich Germany

ISBN: (纸本)9798350302547

The Linux kernel is continuously developing, and the development teams constantly add new versions of libraries with additional features. The cgroups feature of the Linux kernel was recently updated. It is widely used by lightweight virtualization technologies such as Docker or LXC for resource isolation. cgroups underwent a significant revamp from version 1 (v1) to version 2 (v2). Researching the performance difference between these two versions regarding network latencies and throughput enables the usage of containers in time-critical applications for network function virtualization (NFV). Previous work does not consider cgroups as a potential source of latency in NFV in their evaluations. In this paper, we use commodity hard- and software to measure the difference between v1 and v2 in isolation. Our experiments show that the two versions achieve the same degree of isolation. However, the tail latencies of v1 are higher than v2, which can be explained by a more efficient, 2.4% less instruction-consuming implementation of v2. Based on our findings, we recommend using v2 for low-latency, lightweight virtualization network deployments wherever possible.

关键词： low latency container virtualization cgroups network function virtualization

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