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Service function chain network planning through offline, online and infeasibility restoration techniques

COMPUTER networkS 2024年 242卷

作者： Mohamed, Ramy Avgeris, Marios Leivadeas, Aris Lambadaris, Ioannis Chinneck, John Morris, Todd Djukic, Petar Carleton Univ Dept Syst & Comp Engn Ottawa ON Canada ETS Dept Software & Informat Technol Engn Montreal PQ Canada Ciena Ottawa ON Canada

network function virtualization (NFV) and Service function Chaining (SFC) have created a new, flexible, and cost-efficient way of network service offering. Thus, Service (SPs) and Infrastructure Providers (InPs) are updating their product portfolio to incorporate these new technologies. However, placing the network components, called Virtualized network functions (VNFs), that constitute the network services on top of the physical infrastructure creates several resource allocation challenges. This paper offers a networking planning solution tool for SP and InPs to allocate resources according to the expected network demand appropriately. In particular, first, we propose an offline and optimal solution that dimensions and exactly allocates the physical resources according to the estimated workload. Following, mispredicted offline solutions are corrected by various online placement solutions that serve the network workload according to the time of its arrival. Finally, to alleviate any resource mismatch between the total capacity of the physical network and the total requested resources of the expected SFCs, a novel feasibility placement approach is proposed that provides suggestions to the InPs on where to place additional resources. Extensive experimentation shows that the proposed planning tool can efficiently preallocate SFCs under different configuration scenarios, while the feasibility restoration tool provides accurate, timely, and cost-efficient remedy solutions for the InPs.

关键词： Service function chaining network function virtualization network planning Feasibility analysis VNF placement

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Reliability-Oriented and Resource-Efficient Service function Chain Construction and Backup

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IEEE TRANSACTIONS ON network AND SERVICE MANAGEMENT 2021年第1期18卷 240-257页

作者： Wang, Ying Zhang, Leyi Yu, Peng Chen, Ke Qiu, Xuesong Meng, Luoming Kadoch, Michel Cheriet, Mohamed Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China Univ Quebec Ecole Technol Super Synchromedia Lab Montreal PQ H3C 1K3 Canada

In the network function virtualization (NFV) environment, network services are usually provided in the form of service function chains (SFCs), which defines the link order of virtual network functions required in service requests and are mapped to the physical network. Although NFV facilitates the flexible provision of network services, service interruptions may occur as a result of software and hardware failures. Current solutions mostly use the backup method to ensure the reliability of SFCs. However, these methods ignore the SFC construction phase that has an impact on reliability. Besides, the resource efficiency still requires improvement. To address these issues, reliability-oriented SFC construction and backup problems are investigated in this work. First, an instance-sharing and reliable construction algorithm (ISRCA) is proposed to aggregate multiple SFCs into a service function graph (SFG), and perform reliability screening for the SFG set. After mapping the SFG to the physical network, a node-ranking algorithm with centrality and reliability (NRCR) is proposed for backup node selection and backup instance deployment to improve the reliability of SFCs that have not met the requirements. Experimental results demonstrate that under the premise of ensuring reliability, the proposed backup method can reduce the consumption of bandwidth resources by about 11.7%, when combined with the proposed construction method, it can further reduce the backup resources by 13.9%.

关键词： Reliability Software reliability Telecommunication network reliability Optimization Software Resource management Hardware network function virtualization service function chain reliability construction backup

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An Adaptive Service function Chains Mapping With Multi-Task Deep Reinforcement Learning

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IEEE Transactions on network Science and Engineering 2025年

作者： Wei, Wenting Wang, Qingyi Gu, Huaxi Zheng, Danyang Zhang, Ning Wu, Celimuge Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China Southwest Jiaotong University School of Computing and Artificial Intelligence China University of Windsor Department of Electrical and Computer Engineering Canada University of Electro-Communications Meta-Networking Research Center Japan

network function virtualization (NFV) facilitates different virtual network functions (VNF) to be dynamically chained in sequence to offer new services in a flexible, scalable, and cost-effective manner. Recent years have witnessed the increasing diverse service demands from the ever-increasing new applications, which has posed significant challenges to the efficient and sequential execution of VNFs to achieve specific objectives, especially under conditions of shared resources. To address these challenges, substantial efforts have been dedicated to enhancing resource utilization and minimizing the costs associated with service function chains (SFCs), while maintaining high quality of service. However, an overemphasis on cost reduction can sometimes result in network congestion, which ultimately degrades both network performance and service quality. Given the time-varying and unpredictable characteristics of SFCs, it is essential to leverage their temporal features, along with those of network states, for adaptive SFC mapping. In this paper, we introduce an adaptive online SFC mapping algorithm to reduce operational costs and alleviate network congestion. This is achieved through the adaptive allocation of VNFs and the control of traffic routing between them. Our approach incorporates multi-task deep reinforcement learning to manage the coexistence of multiple SFC requests with varying resource requirements. Specifically, we integrate a long short-term memory (LSTM) layer into our model to capture the temporal dynamics of network states and resource demands, thereby enabling more effective long-term planning. To address the issue of reward sparsity, we implement a hierarchical reward mechanism and reward shaping techniques. Experimental results demonstrate that our algorithm achieves near-optimal performance in optimizing service delay, bandwidth consumption, and network congestion, while also ensuring a high acceptance rate for user requests. © 2013 IEEE.

关键词： network function virtualization

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On the Effective Parallelization and Near-Optimal Deployment of Service function Chains

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IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS 2021年第5期32卷 1238-1255页

作者： Luo, Jianzhen Li, Jun Jiao, Lei Cai, Jun Guangdong Polytech Normal Univ Sch Cyber Secur Guangzhou 510665 Peoples R China Univ Oregon Dept Comp & Informat Sci Eugene OR 97403 USA

network operators compose Service function Chains (SFCs) by tying different network functions (e.g., packet inspection, flow shaping, network address translation) together and process traffic flows in the order the network functions are chained. Leveraging the technique of network function virtualization (NFV), each network function can be "virtualized" and decoupled from its dedicated hardware, and therefore can be deployed flexibly for better performance at any appropriate location of the underlying network infrastructure. However, an SFC often incurs high latency as traffic goes through the virtual network functions one after another. In this article, we first design an algorithm that leverages virtual network function dependency to convert an original SFC into a parallelized SFC (p-SFC). Then, to deploy multiple p-SFCs over the network for serving a large number of users, we model the deployment problem as an Integer Linear Program and propose a heuristic, ParaSFC, based on the Viterbi dynamic programming algorithm to estimate each p-SFC's occupation of the bottleneck resources and adjust the processing order of the p-SFCs in order to approximate the optimal solution. Finally, we conduct extensive trace-driven evaluations and exhibit that, compared to the Greedy method and the state-of-the-art CoordVNF method, ParaSFC reduces the average service latency of all the deployed p-SFCs by about 15 percent through parallelization while accommodating more SFC deployment requests over resource-limited networks.

关键词： Heuristic algorithms Servers Quality of service Parallel processing network function virtualization Approximation algorithms Hardware network function virtualization service function chain parallelization deployment quality of service

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Toward a Real Deployment of network Services Orchestration and Configuration Convergence Framework for 5G network Slices

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IEEE network 2021年第1期35卷 242-250页

作者： Afolabi, Ibrahim Bagaa, Miloud Boumezer, Walid Taleb, Tarik Aalto Univ Espoo Finland Aalto Univ Commun & Networking Dept Espoo Finland Aalto Univ Sch Elect Engn Commun & Networking Espoo Finland Aalto Univ Sch Elect Engn Espoo Finland Sejong Univ Seoul South Korea Univ Oulu Oulu Finland

A seamless interworking between network function virtualization (NFV) and software defined networking (SDN) to orchestrate network services for the 5G systems is very fundamental for network slice creation. The orchestration of large scale network slices across multiple administrative as well as technological domains with heterogeneous resources and a distributed form of slice management can benefit from harnessing existing NFV orchestration (NFVO) solutions. In this regard, this article presents a network service orchestration and configuration convergence framework that is capable of providing a large scale network slicing solution for 5G network operators. Using this framework, 5G network operators can orchestrate and configure network slices directly from their infrastructure and that of credible registered slice providers who have resources for the orchestration of only a subset of the overall network slice. The framework is equipped with mechanisms that allow a distributed form of slice configuration and management.

关键词： 5G mobile communication Convergence 3GPP network slicing Software defined networking network function virtualization

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An online distributed approach to network function Placement in NFV-enabled networks

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SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES 2021年第1期46卷 1-18页

作者： Anbiah, Anix Sivalingam, Krishna M. Indian Inst Technol Madras Dept Comp Sci & Engn Chennai Tamil Nadu India

network function Placement (NFP) involves placing virtual network functions (VNFs) on the nodes of a network such that the data that flow through the network are processed by a chain of service functions along their path from source to destination. There are three aspects to this problem: (i) routing the flows efficiently through the network, (ii) placement of the VNFs on the nodes and (iii) steering each flow through a chain of VNFs, known as the service function chain (SFC). Routing must attempt to find "optimal" paths through the network (for e.g., shortest paths), possibly subject to constraints such as path latency and link bandwidth. The VNFs consume resources on the nodes where they are placed and are constrained by the capacity of the nodes. Steering must ensure that each flow has along its path a sequence of VNFs, likely in a certain order. One way to specify this problem is to define a multi-commodity flow problem with additional constraints based on the steering and placement requirements. Simultaneously solving all three aspects of this problem, trying to optimize various parameters and within the various constraints, is a hard problem, with even a simplified version shown to be NP-complete in this paper. Attempting to optimally solve this problem in real time while flows are getting provisioned and de-provisioned in parallel is an intractable problem, especially in large networks. Hence various types of heuristics have been used to solve this problem. In this paper we introduce a distributed, online solution that employs a message-passing protocol for nodes to negotiate the placement of the VNFs, with the minimization of the number of VNF instances being the primary objective. We compare the performance of the solution to that of the theoretically optimal solution and other proposed heuristics on both the Fat-tree topology and the BCube topology. The results show that this solution performs better than other heuristics. The average ratio of the result o

关键词： Software-Defined networks network function virtualization network function Placement distributed

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Intelligent Environment Enabling Autonomous Driving

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IEEE ACCESS 2021年 9卷 32997-33017页

作者： Khan, Manzoor Ahmed UAE Univ UAEU Dept Comp & Network Engn Coll IT Al Ain U Arab Emirates

Automated driving is expected to enormously evolve the transportation industry and ecosystems. Advancement in communications and sensor technologies have further accelerated the realization process of the autonomous driving goals. There are a number of autonomous driving initiatives around the world with varying objectives and scope, e.g. vehicle perception in a controlled environment or highway settings. Autonomous driving in a more complex environment with mixed traffic poses major challenges. The solutions for such environments is the focus of this paper. We start with a quick overview of current autonomous driving development activities worldwide. We then discuss the solution concept for autonomous driving in urban environments and its enabling components, e.g. road digitization and flexible communication infrastructure, to realize an urban autonomous driving testbed. We highlight the major challenges hindering the realization use-cases of Level 5 autonomous driving. Solution sketches to address these or similar changes are briefly discussed. We also implement some elements of the solution approaches on the real test-road. We demonstrate an artificial intelligence based approach for the analysis of real traffic data measured on the testbed. We implement approaches for predicting the network resource demands and allocation, which are crucial for realizing the use-cases of autonomous driving in complex environments. For the experiments, real data from the test-road is used. Results show that traffic patterns and resource demands are predicted accurately. These experiments are expected to instrumental for realizing other use-cases of autonomous driving.

关键词： Autonomous vehicles Roads Testing Vehicle dynamics Urban areas Automation Licenses Autonomous systems intelligent vehicles network function virtualization

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NFV-Enabled IoT Service Provisioning in Mobile Edge Clouds

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2021年第5期20卷 1892-1906页

作者： Xu, Zichuan Gong, Wanli Xia, Qiufen Liang, Weifa Rana, Omer F. Wu, Guowei Dalian Univ Technol Sch Software Dalian 116024 Peoples R China Dalian Univ Technol Key Lab Ubiquitous Network & Serv Software Liaoni Dalian 116024 Peoples R China Dalian Univ Technol Int Sch Informat Sci & Engn Dalian 116024 Peoples R China Australian Natl Univ Res Sch Comp Sci Canberra ACT 2601 Australia Cardiff Univ Performance Engn Cardiff CF10 3AT Wales

Conventional Internet of Things (IoT) applications involve data capture from various sensors in environments, and the captured data then is processed in remote clouds. However, some critical IoT applications (e.g., autonomous vehicles) require a much lower response latency and more secure guarantees than those offered by remote clouds today. Mobile edge clouds (MEC) supported by the network function virtualization (NFV) technique have been envisioned as an ideal platform for supporting such IoT applications. Specifically, MECs enable to handle IoT applications in edge networks to shorten network latency, and NFV enables agile and low-cost network functions to run in low-cost commodity servers as virtual machines (VMs). One fundamental problem for the provisioning of IoT applications in an NFV-enabled MEC is where to place virtualized network functions (VNFs) for IoT applications in the MEC, such that the operational cost of provisioning IoT applications is minimized. In this paper, we first address this fundamental problem, by considering a special case of the IoT application placement problem, where the IoT application and VNFs of each service request are consolidated into a single location (gateway or cloudlet), for which we propose an exact solution and an approximation algorithm with a provable approximation ratio. We then develop a heuristic algorithm that controls the resource violation ratios of edge clouds in the network. For the IoT application placement problem for IoT applications where their VNFs can be placed to multiple locations, we propose an efficient heuristic that jointly places the IoT application and its VNFs. We finally study the performance of the proposed algorithms by simulations and implementations in a real test-bed, Experimental results show that the performance of the proposed algorithms outperform their counterparts by at least 10 percent.

关键词： Internet of Things Cloud computing Logic gates Approximation algorithms Data centers Mobile computing Delays Mobile edge clouds network function virtualization Internet of Things (IoT) application approximation algorithms VNF placement algorithm design

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Edge-to-Cloud Collaborative for QoS Guarantee of Smart Cities

Edge-to-Cloud Collaborative for QoS Guarantee of Smart Citie...

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IFAC Workshop on Control for Smart Cities (CSC)

作者： Wang, Jiaju Jian, Wei Fu, Baochuan Suzhou Univ Sci & Technol Suzhou 215009 Peoples R China

With the rapid development of big data, cloud computing, mobile Internet and other new-generation information technologies, smart cities, carry more and more intelligent applications, and put forward higher requirements for data processing capacity and network service quality. The integration system of Edge-to-Cloud collaboration provides a feasible method to effectively improve network performance to adapt to the changing needs of users. However, the existing network management mechanism is difficult to adapt to the actual demand changes due to the characteristics of the edge-cloud fusion system, such as device diversity, location complexity and resource dynamics. This article to the idea of sliding mode control function of network virtualization technology and network, the study method and collaborative optimization theory as the foundation, of the application of static and dynamic models of the intelligence cities, fault prediction and fault tolerant management mechanism, task scheduling and resource allocation adaptive collaborative optimization mechanism, to ensure that the cities network real-time, reliability, and security, At the same time, combined with the smart campus platform of our school, the real-time performance and effectiveness of the network are tested and evaluated, providing a case demonstration for the intelligent application of smart cities. This project will further enrich and improve the theoretical system of end-to-end cloud collaborative optimization and provide new means and methods for intelligent cities network QoS(Quality of Service) guarantee. Copyright (C) 2022 The Authors.

关键词： Smart City Edge-to-Cloud Collaboration network function virtualization Task Scheduling Resource Allocation Task Offloading

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An efficient automatic testing framework for NFV systems

An efficient automatic testing framework for NFV systems

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2022 International Conference on Cloud Computing, Performance Computing, and Deep Learning, CCPCDL 2022

作者： Zhu, Yuanrui Lin, Xiancheng Zhu, Wanyi Liu, Rongkai Fan, Yongbing Research Institute of China Telecom Co. Ltd Guangdong Guangzhou510000 China

ISBN: (纸本)9781510655867

NFV systems are becoming more complicated with various of software modules, vendors and interfaces introduced. Testing such systems is very time consuming and requires lots of expertise. In this paper, we propose an efficient automatic testing framework to simplify and speedup the testing process. There are two critical components in this framework, i.e., a structured and reusable test case format and an abstraction layer to adapt different testing tools. Based on this framework, a tester can quickly compose the test cases by just setting the corresponding parameters of the test tools and target components. After this setting, the framework will automatically arrange the testing order and invoke the testing tools to fulfil the test. The experiment on real systems shows that our framework can greatly improve the testing efficiency. © 2022 SPIE.

关键词： network function virtualization

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