Service Function Chain Migration in LEO Satellite Networks

With the advancements of software defined network(SDN)and network function virtualization(NFV),service function chain(SFC)placement becomes a crucial enabler for flexible resource scheduling in low earth orbit(LEO)satellite networks.While due to the scarcity of bandwidth resources and dynamic topology of LEO satellites,the static SFC placement schemes may cause performance degradation,resource waste and even service failure.In this paper,we consider migration and establish an online migration model,especially considering the dynamic topology.Given the scarcity of bandwidth resources,the model aims to maximize the total number of accepted SFCs while incurring as little bandwidth cost of SFC transmission and migration as possible.Due to its NP-hardness,we propose a heuristic minimized dynamic SFC migration(MDSM)algorithm that only triggers the migration procedure when new SFCs are rejected.Simulation results demonstrate that MDSM achieves a performance close to the upper bound with lower complexity.

Service Function Chain Deployment Algorithm Based on Multi-Agent Deep Reinforcement Learning

Aiming at the rapid growth of network services,which leads to the problems of long service request processing time and high deployment cost in the deployment of network function virtualization service function chain(SFC)under 5G networks,this paper proposes a multi-agent deep deterministic policy gradient optimization algorithm for SFC deployment(MADDPG-SD).Initially,an optimization model is devised to enhance the request acceptance rate,minimizing the latency and deploying the cost SFC is constructed for the network resource-constrained case.Subsequently,we model the dynamic problem as a Markov decision process(MDP),facilitating adaptation to the evolving states of network resources.Finally,by allocating SFCs to different agents and adopting a collaborative deployment strategy,each agent aims to maximize the request acceptance rate or minimize latency and costs.These agents learn strategies from historical data of virtual network functions in SFCs to guide server node selection,and achieve approximately optimal SFC deployment strategies through a cooperative framework of centralized training and distributed execution.Experimental simulation results indicate that the proposed method,while simultaneously meeting performance requirements and resource capacity constraints,has effectively increased the acceptance rate of requests compared to the comparative algorithms,reducing the end-to-end latency by 4.942%and the deployment cost by 8.045%.

Risk-Balanced Routing Strategy for Service Function Chains of Cyber-Physical Power System Considering Cross-Space Cascading Failure

Cyber-physical power system(CPPS)has significantly improved the operational efficiency of power systems.However,cross-space cascading failures may occur due to the coupling characteristics,which poses a great threat to the safety and reliability of CPPS,and there is an acute need to reduce the probability of these failures.Towards this end,this paper first proposes a cascading failure index to identify and quantify the importance of different information in the same class of communication services.On this basis,a joint improved risk-balanced service function chain routing strategy(SFC-RS)is proposed,which is modeled as a robust optimization problem and solved by column-and-constraint generation(C-CG)algorithm.Compared with the traditional shortest-path routing algorithm,the superiority of SFC-RS is verified in the IEEE 30-bus system.The results demonstrate that SFC-RS effectively mitigates the risk associated with information transmission in the network,enhances information transmission accessibility,and effectively limits communication disruption from becoming the cause of cross-space cascading failures.

Multi-Path Service Function Chaining for Mobile Surveillance of Animal Husbandry

Animal husbandry is the pillar industry in some ethnic areas of China.However,the communication/networking infrastructure in these areas is often underdeveloped,thus the difficulty in centralized management,and challenges for the effective monitoring.Considering the dynamics of the field monitoring environment,as well as the diversity and mobility of monitoring targets,traditional WSN(Wireless Sensor Networks)or IoT(Internet of Things)is difficult to meet the surveillance needs.Mobile surveillance that features the collaboration of various functions(camera,sensing,image recognition,etc.)deployed on mobile devices is desirable in a volatile wireless environment.This paper proposes the service function chaining for mobile surveillance of animal husbandry,which orchestrates multi-path multifunction(MPMF)chains to help mobile devices to collaborate in complex surveillance tasks,provide backup chains in case the primary service function chain fails due to mobility,signal strength,obstacle,etc.,and make up for the defects of difficult deployment of monitoring facilities in ethnic areas.MPMF algorithmmodels both mobile devices and various functions deployed on them as abstract graph nodes,so that chains that are required to traverse various functions and hosting mobile devices can be orchestrated in a single graphbased query through modified and adapted Dijkstra-like algorithms,with their cost ordered automatically.Experiment results show that the proposed MPMF algorithm finds multiple least-costly chains that traverse demanded functions in a timely fashion on Raspberry Pi-equipped mobile devices.

软件定义并行多径SFC编排

网络功能虚拟化(Network Functions Virtualization, NFV)技术可以通过动态实例化以及根据随时间变化的服务需求去动态地部署虚拟网络功能。基于NFV的多域网络切片中服务功能链(Service Function Chaining, SFC)的编排问题研究缺乏考虑多域场景,大多数启发式算法仅仅考虑了上界,SFC映射策略无法满足低时延高可靠要求。建立了面向并行业务流服务时延优化的数学模型,并进一步基于拉格朗日松弛法提出了一种考虑了下界的启发式SFC映射策略,可以有效地降低时延,提高服务的可靠性。与多租户边缘网络中可靠的SFC编排算法以及多路径低延迟SFC编排算法相比,所提算法平均包交付率分别提升了3.3%和7.4%,平均资源消耗分别降低了9%和19.2%。

Dynamic Backup Sharing Scheme of Service Function Chains in NFV

Service function chains(SFC)mapping takes the responsibility for managing virtual network functions(VNFs).In SFC mapping,existing solutions duplicate VNFs with redundant instances to provide high availability in response to failures.However,as a compromise,these solutions result in high resource consumption due to device maintenance.In this paper,we propose a novel method named dynamic backup sharing(DBS)that allows SFCs to dynamically share backups to reduce resource consumption.DBS formulates the problem of sharing backups among different VNFs as an integer linear programming(ILP).Thereafter,we design a novel online algorithm based on dynamic programming to solve the problem.The experimental results indicate that DBS outperforms state-ofthe-art works by reducing resource consumption and improving the number of accepted requests.

Service Function Chain in Small Satellite-Based Software Defined Satellite Networks

Software Defined Satellite Networks(SDSN) are proposed to solve the problems in traditional satellite networks, such as time-consuming configuration and inflexible traffic scheduling. The emerging application of small satellite and research of SDSN make it possible for satellite networks to provide flexible network services. Service Function Chain(SFC) can satisfy this need. In this paper, we are motivated to investigate applying SFC in the small satellite-based SDSN for service delivery. We introduce the structure of the multi-layer constellation-based SDSN. Then, we describe two deployment patterns of SFC in SDSN, the Multi-Domain(MD) pattern and the Satellite Formation(SF) pattern. We propose two algorithms, SFP-MD, and SFP-SF, to calculate the Service Function Path(SFP). We implement the algorithms and conduct contrast experiments in our prototype. Finally, we summarize the applicable conditions of two deployment patterns according to the experimental results in terms of hops, delay, and packet loss rate.

Service Function Chain Orchestration across Multiple Clouds

Network function virtualization is a new network concept that moves network functions from dedicated hardware to software-defined applications running on standard high volume severs. In order to accomplish network services, traffic flows are usually processed by a list of network functions in sequence which is defined by service function chain. By incorporating network function virtualization in inter-data center(DC) network, we can use the network resources intelligently and deploy network services faster. However, orchestrating service function chains across multiple data centers will incur high deployment cost, including the inter-data center bandwidth cost, virtual network function cost and the intra-data center bandwidth cost. In this paper, we orchestrate SFCs across multiple data centers, with a goal to minimize the overall cost. An integer linear programming(ILP) model is formulated and we provide a meta-heuristic algorithm named GBAO which contains three modules to solve it. We implemented our algorithm in Python and performed side-by-side comparison with prior algorithms. Simulation results show that our proposed algorithm reduces the overall cost by at least 21.4% over the existing algorithms for accommodating the same service function chain requests.

Virtualizing Network and Service Functions: Impact on ICT Transformation and Standardization

Virtualization of network/service functions means time sharing network/service（and affiliated）resources in a hyper speed manner.The concept of time sharing was popularized in the 1970s with mainframe computing.The same concept has recently resurfaced under the guise of cloud computing and virtualized computing.Although cloud computing was originally used in IT for server virtualization,the ICT industry is taking a new look at virtualization.This paradigm shift is shaking up the computing,storage,networking,and ser vice industries.The hope is that virtualizing and automating configuration and service management/orchestration will save both capes and opex for network transformation.A complimentary trend is the separation（over an open interface）of control and transmission.This is commonly referred to as software defined networking（SDN）.This paper reviews trends in network/service functions,efforts to standardize these functions,and required management and orchestration.

Research on Service Function Chain Orchestrating Algorithm Based on SDN and NFV

Software defined network(SDN)and network function virtualization(NFV)have become a new paradigm of a new generation of network architecture.SDN and NFV can effectively improve the flexibility of deploying and managing service function chains(SFCs).By combining SDN and NFV and applying them to the resource orchestration problem of SFC deployment,the three-tier architecture consisting of SDN controller,network function virtualization and physical underlying computing resource layer in the process of heterogeneous network resource mapping is considered.And an optimization algorithm for active control resources based on SDN and NFV is proposed.Firstly,the user’s utility is modeled by the multistandard aggregated multi-criteria utility algorithm,and the optimization goal is transformed into the problem of maximizing the user’s utility.Then the controller,based on the algorithm’s prediction of the future state and realtime monitoring of the network utilization,makes decisions and issues control commands for the arriving SFC requests,based on which it occupies the underlying resources held by the virtualized network function(VNF).The simulation results show that,compared with the static timing resource allocation algorithm,the active control resource deployment algorithm proposed in the article has better performance in terms of resource utilization,acceptance rate,and user creation utility.

SFC Design and VNF Placement Based on Traffic Volume Scaling and VNF Dependency in 5G Networks

The development of Fifth-Generation(5G)mobile communication technology has remarkably promoted the spread of the Internet of Things(IoT)applications.As a promising paradigm for IoT,edge computing can process the amount of data generated by mobile intelligent devices in less time response.Network Function Virtualization(NFV)that decouples network functions from dedicated hardware is an important architecture to implement edge computing,deploying heterogeneous Virtual Network Functions(VNF)(such as computer vision,natural language processing,intelligent control,etc.)on the edge service nodes.With the NFV MANO(Management and Orchestration)framework,a Service Function Chain(SFC)that contains a set of ordered VNFs can be constructed and placed in the network to offer a customized network service.However,the procedure of NFV orchestration faces a technical challenge in minimizing the network cost of VNF placement due to the complexity of the changing effect of traffic volume and the dependency on theVNFrelationship.To this end,we jointly optimize SFC design and VNF placement to minimize resource cost while taking account of VNF dependency and traffic volume scaling.First,the problem is formulated as an Integer Linear Programming(ILP)model and proved NPhard by reduction from Hamiltonian Cycle problem.Then we proposed an efficient heuristic algorithm called Traffic Aware and Interdependent VNF Placement(TAIVP)to solve the problem.Compared with the benchmark algorithms,emulation results show that our algorithm can reduce network cost by 10.2%and increase service request acceptance rate by 7.6%on average.

AdaptNF: Adaptive service chain scheduling with stateless migration and NF consolidation

The combination of network function virtualization and software-defined networking allows various network functions to process flows according to their characteristics and requirements.Due to the highly dynamic nature of the workload,the network infrastructure needs to properly schedule the underlying resources in order to respond to workload changes in a timely manner.However,the existing NFV platform lacks a comprehensive solution for how to scale under workload variation,which may seriously hurt the overall system performance.To improve the scalability of the NFV platform and ensure consistent high performance under dynamic workloads,we propose AdaptNF,a novel NFV platform designed to support a combination of course-grained and fine-grained resource scheduling strategies.To deal with resource imbalance,which is the essential scheduling problem that leads to insufficient NFV performance,AdaptNF adopts a novel algorithm that can efficiently balance the workload among multiple network function instances through stateless flow migration.Our controlled experiments show that the AdaptNF scheme can optimize resource allocation and ensure outstanding performance after scaling.In terms of network throughput and latency,AdaptNF significantly improves the performance of the underlying NFV platform.

Dynamic Security SFC Branching Path Selection Using Deep Reinforcement Learning

Security service function chaining(SFC)based on software-defined networking(SDN)and network function virtualization(NFV)technology allows traffic to be forwarded sequentially among different security service functions to achieve a combination of security functions.Security SFC can be deployed according to requirements,but the current SFC is not flexible enough and lacks an effective feedback mechanism.The SFC is not traffic aware and the changes of traffic may cause the previously deployed security SFC to be invalid.How to establish a closed-loop mechanism to enhance the adaptive capability of the security SFC to malicious traffic has become an important issue.Our contribution is threefold.First,we propose a secure SFC path selection framework.The framework can accept the feedback results of traffic and security service functions in SFC,and dynamically select the opti-mal path for SFC based on the feedback results.It also realizes the automatic deployment of paths,forming a complete closed loop.Second,we expand the protocol of SFC to realize the security SFC with branching path,which improve flexibility of security SFC.Third,we propose a deep reinforcement learning-based dynamic path selection method for security SFC.It infers the optimal branching path by analyzing feedback from the security SFC.We have experimented with Distributed Denial of Service(DDoS)attack detection modules as security service functions.Experimental results show that our proposed method can dynamically select the optimal branching path for a security SFC based on traffic features and the state of the SFC.And it improves the accuracy of the overall malicious traffic detection of the security SFC and significantly reduces the latency and overall load of the SFC.

结合深度强化学习的边缘计算网络服务功能链时延优化部署方法

该文针对边缘网络资源受限且对业务流端到端时延容忍度低的问题,结合深度强化学习与基于时延的Dijkstra寻路算法提出一种面向时延优化的服务功能链(SFC)部署方法。首先,设计一种基于注意力机制的序列到序列(Seq2Seq)代理网络和基于时延的Dijkstra寻路算法,用于产生虚拟网络功能(VNF)的部署以及服务SFC的链路映射,同时考虑了时延优化模型的约束问题,采用拉格朗日松弛技术将其纳入强化学习目标函数中;其次,为了辅助网络代理快速收敛,采用基线评估器网络评估部署策略的预期奖励值;最后,在测试阶段,通过贪婪搜索及抽样技术降低网络收敛到局部最优的概率,从而改进模型的部署。对比实验表明,该方法在网络资源受限的情况下,比First-Fit算法与TabuSearch算法的时延分别降低了约10%和86.3%,且较这两种算法稳定约74.2%与84.4%。该方法能较稳定地提供更低时延的端到端服务,使时延敏感类业务获得更好体验。

基于资源感知的多域服务功能链编排成本优化

网络功能虚拟化技术的兴起使得实例化为服务功能链(SFC)的网络服务能够共享基底网络,缓解了传统网络体系结构僵化的问题.然而,网络中大量服务请求给多域SFC编排带来了新的挑战.首先由于域内网络资源信息及内部策略的保密性,使得多域SFC的编排更为复杂.其次多域SFC编排要确定最佳候选编排域集,先前的研究较少考虑域间负载的均衡性,对服务接受率造成了消极影响.此外跨网络域编排服务请求对服务的成本和响应时间提出了更严格的要求.为解决上述挑战,在本文中,我们首先针对多域网络隐私性需求,提出了域级图的构造方法;然后基于域间负载均衡提出了域权重的计算方法进行SFC编排域的选择;最后,针对多域网络成本和响应时间需求,提出编排算法.实验结果表明,提出的算法有效地权衡了平均服务成本和接受率,并且在服务平均响应时间方面也得到了优化.

服务投入质量与制造业功能升级

通过将功能升级定义为产业生产重心向非制造性高端生产环节转移,本文使用多国制造业子行业面板数据研究了服务投入质量对制造业功能升级的影响。研究结果显示,服务投入质量提高能够有效促进制造业功能升级,尤其是能够有效促进制造业生产重心向管理和研发功能倾斜。异质性研究表明,相较于国外服务投入,国内服务投入质量提高对功能升级的影响更显著,高技能制造业受到服务投入质量提高的促进效果更好。机制分析表明,创新和技术溢出效应是服务投入质量影响功能升级的可能渠道。本文为制造业投入服务质量与功能升级的关系提供了跨国视角的研究,为价值链重构背景下破解西方国家功能锁定等问题提供了相应的实证借鉴。

软件定义无线网络异构服务功能链低功耗部署方法

受到节点性能以及功耗方面的限制,在对无线网络异构服务功能链进行部署时,通常会因缺乏节点重要程度评估而导致部署效果不佳。对此,提出软件定义无线网络异构服务功能链低功耗部署方法。首先通过对网络协议内容进行获取,实现拓扑结构感知,并构建出节点重要度与节点链路数目之间的相关关系,对网络节点的重要度进行计算。然后将原始服务功能链拆分为多个独立的服务功能,并以节点综合度最高以及网络功耗最低构建出的目标函数作为映射方案求解途径,将服务功能映射到物理节点上。利用SDN控制器的编程接口,将功能链分解与映射的结果转化为网络配置指令。最后构建交换机的流量需求信息与待部署节点之间的映射关系,从而实现低功耗部署。在实验中,对提出的服务功能链部署方法进行了部署效果的检验。最终的测试结果表明,采用提出的方法对服务功能链进行模拟部署后,软件定义无线网络的功耗值更低,具备较为理想的部署效果。

一种基于近端策略优化的服务功能链部署算法

针对网络功能虚拟化(NFV)环境下高维度服务功能链(SFC)部署的高可靠低成本问题,该文提出了一种基于近端策略优化的服务功能链部署算法(PPO-ISRC)。首先综合考虑底层物理服务器特征和服务功能链特征,将服务功能链部署建模为马尔可夫决策过程,然后,以最大化服务率和最小化资源消耗为优化目标设置奖励函数,最后,采用近端策略优化方法对服务功能链部署策略求解。仿真实验结果表明,与启发式算法(FFD)和深度确定性策略梯度算法(DDPG)相比,所提算法具有收敛速度快,稳定性高的特点。在满足服务质量的要求下,降低了部署成本,并提高了网络服务可靠性。

GAT-IL:一种基于图注意力网络与模仿学习的服务功能链部署方法

网络功能虚拟化通过将网络功能从专用硬件设备迁移到商用服务器上运行的软件中间盒中,简化了网络服务的配置和管理.在网络功能虚拟化的环境下,由一系列有序的虚拟网络功能组成的服务功能链正在成为承载网络服务的主流形式.将底层物理网络资源分配给服务功能链的需求称为服务功能链部署问题.对于基础设施提供商来说,在有限的资源条件下获得长期高回报是一个重要的挑战.本文形式化定义了服务功能链部署问题,提出了一种基于图注意力网络与模仿学习的服务功能链部署方法(Graph Attention Network and Imitation Learning,GAT-IL).该方法使用图注意力网络评估每个物理服务器的放置潜力,通过蒙特卡洛树搜索方法给出专家示范,并采用模仿学习方法进行智能体的训练,融入集束搜索策略优化解空间.大量的实验结果表明,本文提出的GAT-IL方法在平均收益代价比和接受率的性能指标上均优于现有代表性算法.

航空信息网络服务功能链请求调度策略

为解决航空信息网络场景下业务突发、拓扑结构动态变化以及资源有限所带来的资源利用效率低下问题,针对服务功能链请求(Service Function Chain Requirement,SFCR)高效调度的难题,提出一种网络功能虚拟化的服务功能链调度算法。算法依据SFCR与平台的相关性进行映射,提高服务器处理效率并有效减少虚拟网络功能实例化数量及整合平台资源;综合考虑时延和流量影响对网络功能实例进行整合迁移,降低网络能耗同时提升网络资源利用率。仿真结果表明,在满足时延需求条件下,新方法在运行平台数量、SFCR接受率、网络资源消耗等方面具有较好的优化性能,适用于解决航空信息网络场景下的SFCR调度问题。