An Elastic Sub-carrier and Power Allocation Algorithm Enabling Wireless Network Virtualization

Wireless mobile network virtualization enables physical mobile network operators (PMNO) to partition their network resources into smaller slices and assign each slice to an individual virtual mobile network operator and then manages these virtual networks in a more dynamic and cost-effective fashion. How a PMNO allocates resources to individual slices while ensuring resource elasticity is a key issue. This paper presents a resource allocation algorithm in such a network virtualization scenario where resource considered here includes both sub-carriers and transmission power. The overall algorithm involves the following two major processes: firstly to virtualize a physical wireless network into multiple slices each representing a virtual network, where resources are allocated elastically based on traffic loads and channel state information during virtualization; secondly, to carry out physical resource allocation within each virtual network (or slice). In particular the paper adopts orthogonal frequency division multiplexing as its physical layer to achieve more efficient resource utilization. A multi-step dynamic optimization approach is proposed to achieve sub-carrier allocation using binary integer programming and power allocation using nonlinear programming. The aim is to achieve the following design goals: virtual network isolation, and resource efficiency. The simulation results show that the above goals have been achieved.     

SDN试验床网络虚拟化切片机制综述

未来网络体系架构和关键技术的研究需要灵活开放的测试验证环境,基于传统分布式的网络架构难以达到动态虚拟化、有效管控和新协议灵活部署的需求。随着软件定义网络（SDN）技术的出现和发展,上述问题找到了有效的解决途径,因此,基于SDN构建网络试验床成为了近年来该领域的主流研究方向之一。其中,基于SDN的网络虚拟化切片技术更是试验床中的核心支撑技术,可以根据不同试验的需求切分物理网络资源,从而提供并行、独立的网络环境。将重点研究基于SDN的试验床中使用的网络虚拟化切片机制,从“流量识别和切片网络标识”、“虚拟节点抽象”和“虚拟链路抽象”这3个关键技术出发,对当前基于SDN试验床中的典型网络虚拟化切片机制进行介绍与分析,并总结了该领域未来可行的研究方向。     

非正交多址接入系统中基于受限马尔科夫决策过程的网络切片虚拟资源分配算法

针对无线接入网络切片虚拟资源分配优化问题,该文提出基于受限马尔可夫决策过程(CMDP)的网络切片自适应虚拟资源分配算法。首先,该算法在非正交多址接入(NOMA)系统中以用户中断概率和切片队列积压为约束,切片的总速率作为回报,运用受限马尔可夫决策过程理论构建资源自适应问题的动态优化模型;其次定义后决策状态,规避最优值函数中的期望运算;进一步地,针对马尔科夫决策过程(MDP)的“维度灾难”问题,基于近似动态规划理论,定义关于分配行为的基函数,替代决策后状态空间,减少计算维度;最后设计了一种自适应虚拟资源分配算法,通过与外部环境的不断交互学习,动态调整资源分配策略,优化切片性能。仿真结果表明,该算法可以较好地提高系统的性能,满足切片的服务需求。     

A QoS-Aware Joint Power and Subchannel Allocation Algorithm for Mobile Network Virtualization

Mobile network virtualization is a promising technology due to its flexibility and feasibility. Since it enables physical resources abstraction and sharing, the overall resource inefficiency can be reduced dramatically. By means of virtualization, mobile service providers can share their physical resources with multiple virtual network operators. In this paper, a joint power and subchannel allocation algorithm for mobile network virtualization (MNV) with quality of services support is proposed. It presents a resource allocation scheme for orthogonal frequency division multiple access-based MNV with multiple virtual network operators. An optimal solution is provided to maximize the total data rate of both infrastructure providers and virtual network operators. Numerical results have shown that the proposed resource allocation algorithm improves the overall performance.

     

面向多业务场景的端到端网络切片安全部署算法

5G移动通信中,网络切片(NS)的引入成功解决了不同业务场景的网络资源分配不均问题.针对传统算法无法满足5G网络的多业务场景切片安全部署问题,该文提出一种针对于多业务场景的端到端网络切片安全需求(NSR)部署算法.首先,针对切片部署过程中节点的安全性进行了定义;其次,根据节点的安全性进行排序和映射,在此基础上,以最小化...     

An efficient resource allocation to improve QoS of 5G slicing networks using general processor sharing‐based scheduling algorithm

Fifth generation (5G) slicing is an emerging technology for software‐defined networking/network function virtualization–enabled mobile networks. Improving the utilization and throughput to meet the quality of service (QoS) requirements of 5G slicing is very important for the operators of mobile networks. With growing data traffic from different applications of numerous smart mobile devices having several QoS requirements, we expect networks to face problems of congestion and overload that prevent the effective functioning of a radio access network (RAN). This paper proposes a more effective packet‐based scheduling scheme for data traffic by 5G slicing with two operation modes for improving the resource utilization of 5G cloud RAN and providing an efficient isolation of the 5G slices. These two operation modes are referred to as static sharing resource (SSR) scheme and dynamic sharing resources (DSR) scheme. The SSR scheme is a modified version of an existing method. The goal of this approach is to reallocate the shared available resources of 5G network fairly and maximize the utilization of bandwidth while protecting a 5G slice from overwhelming other 5G slices. Throughput and delays of the system model are also discussed to show its performance limits. On the basis of the simulation outcomes, we observed that the proposed DSR scheme outperforms the SSR scheme in terms of provided delay and throughput. In addition, the token bucket parameters together with the assigned capacity weight for each slice can be selected and configured based on the required QoS. Finally, a good estimate for the maximum delay bounds of the slices is provided by the derived theoretical delay bound.     

Incentive Scheme for Slice Cooperation Based on D2D Communication in 5G Networks

In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.     

An elastic resource allocation algorithm enabling wireless network virtualization

Following the wired network virtualization, virtualization of wireless networks becomes the next step aiming to provide network or infrastructure providers with the ability to manage and control their networks in a more dynamic fashion. The benefit of the wireless mobile network virtualization is a more agile business model where virtual mobile network operators (MNOs) can request and thus pay physical MNOs in a more pay‐as‐you‐use manner. This paper presents some resource allocation algorithms for joint network virtualization and resource allocation of wireless networks. The overall algorithm involves the following two major processes: firstly, to virtualize a physical wireless network into multiple slices, each representing a virtual network, and secondly, to carry out physical resource allocation within each virtual network (or slice). In particular, the paper adopts orthogonal frequency division multiplexing (OFDM) as its physical layer to achieve more efficient resource utilization. Therefore, the resource allocation is conducted in terms of sub‐carriers. Although the motivation and algorithm design are based on IEEE 802.16 or WiMAX networks, the principle and algorithmic essence are also applicable to other OFDM access‐based wireless networks. The aim was to achieve the following design goals: virtual network isolation and resource efficiency. The latter is measured in terms of network throughput and packet delivery ratio. The simulation results show that the aforementioned goals have been achieved. Copyright © 2012 John Wiley & Sons, Ltd.     

LTE无线网络虚拟化中切片调度策略

研究了未来移动通信网络切片机制,针对LTE系统下行在基站内建立媒体接入控制(MAC)层流级别的切片调度器,使得运营商之间可以按照预设比例共享资源.运营商作为切片的拥有者可以根据不同的服务等级协议(SLA)来对其资源比例进行设定.比较固定切片与网络虚拟化基片(NVS)框架下切片的资源块利用率,进行了系统级仿真实验.相对于固定切片方法,NVS方法在不同切片间用户相互隔离的情况下有更好的资源利用率.此外,针对实时(RT)业务和非实时(NRT)业务在时延上的差异建立业务切片,定制化地选择其调度算法策略,从而在降低分组丢失率的同时提升整个系统的性能.     

H-CRAN网络下联合拥塞控制和资源分配的网络切片动态资源调度策略

针对异构云无线接入网络(H-CRAN)网络下基于网络切片的在线无线资源动态优化问题,该文通过综合考虑业务接入控制、拥塞控制、资源分配和复用,建立一个以最大化网络平均和吞吐量为目标,受限于基站(BS)发射功率、系统稳定性、不同切片的服务质量(QoS)需求和资源分配等约束的随机优化模型,并进而提出了一种联合拥塞控制和资源分配的网络切片动态资源调度算法。该算法会在每个资源调度时隙内动态地为性能需求各异的网络切片中的用户分配资源。仿真结果表明,该文算法能在满足各切片用户QoS需求和维持网络稳定的基础上,提升网络整体吞吐量,并且还可通过调整控制参量的取值实现时延和吞吐量间的动态平衡。     

Method of network slicing deployment based on performance-aware

In order to deal with the performance degradation caused by resource contention due to the sharing of physical resources between VNF in the network slicing,a network slicing deployment method based on performance-awareness was proposed.When deploying network slice instances,first two-phase deployment that mapping virtual nodes was adopted,and then virtual links were mapped.In the virtual nodes mapping phase,the VNF performance influences factor was defined from the perspective of resource supply and demand to quantify the degree of VNF performance impact.Then the sum of the performance influence factors of all VNF on the deployable physical server was found in the network slice instance,the physical server with the smallest sum of performance influence factors was used as the mapping location,and the simulated annealing-discrete particle swarm algorithm was used to find the nodes mapping result.In the virtual links mapping phase,the shortest path algorithm was used to obtain the link mapping result.The simulation results show that the proposed method reduces the impact of other network slices on its own service performance.     

基于计算、存储、传送资源融合化的新型网络虚拟化架构

5G与边缘计算等应用场景的兴起,使得计算、存储等基础IT资源离散部署与多级部署成为一大发展趋势,如何结合网络基础设施为用户提供更为便捷的、定制化的专属服务,提高整体资源利用率,成为网络技术发展的新方向。重点分析了网络虚拟化的特征与发展、资源发展与融合趋势以及新兴业务对资源供给新需求等,提出了一种基于多维资源融合化的网络虚拟化架构,即通过在网络虚拟化架构中引入资源发现与资源交易过程,将多方、异构的资源有机整合成统一资源平面,在此基础上根据用户需求进行资源切割与虚拟化,以适应新兴业务对资源需求快速灵活的特点,并能够有效提高资源利用效率,降低运营成本。由于资源联合优化涉及多个领域的研究,网络虚拟化架构将随着业务需求与商业模式的发展而不断完善,以期为未来业务发挥重要作用。     

面向服务的车辆网络切片协调智能体设计

针对现有研究中缺乏对车辆网络切片的部署和管理，该文设计了车辆网络切片架构中的切片协调智能体。首先基于K-means++聚类算法将车联网通信业务根据相似度进行聚类并映射到对应的切片中。其次，在考虑应用场景间的时空差异导致的无线资源利用不均衡现象，提出了共享比例公平方案以实现对无线资源的高效及差异化利用。最后，为了保证切片服务需求，采用线性规划障碍方法求解最优的切片权重分配，使切片负载变化容忍度最大化。仿真结果表明，共享比例公平方案相比于静态切片方案平均比特传输时延(BTD)更小，在每切片用户数为30的情况下均匀分布用户负载场景中二者的BTD增益为1.4038，且在不同的用户负载分布场景下都能求出最优的切片权重分配。     

5G端到端网络切片进展与挑战分析

随着5G端到端网络切片商用部署的逐步推进,在切片实施过程中遇到一些问题和挑战,因此亟需对其当前的研究进展及挑战进一步分析.从对5G端到端网络切片的系统性论述切入,首先介绍了5G网络切片的架构和功能,之后梳理了目前国内外标准组织对网络切片及其增强技术的研究进展,最后识别并深入分析了端到端网络切片面临的挑战,包括SLA保障...     

基于时空特征提取的智能网络切片算法

5G网络作为新一代的移动通信网络,提供了差异多样的各类业务服务,而通过网络切片可以将5G网络的资源虚拟化并更为有效地分配给各类服务.然而,当用户的服务需求发生变化时,需要及时地进行切片资源的重新分配和管理.为了准确适配业务需求的时空变化,提升切片性能,考虑采用深度强化学习的人工智能算法对切片资源进行实时管理,提出了基于...     

Mapping Application Requirements to Virtualization-Enabled Software Defined WSN

With the emergence of resource powerful sensor nodes, the concept of WSN virtualization is gaining increasing attention from the research community and the industry. One approach to achieve WSN virtualization is to exploit the capabilities of individual sensor nodes to execute tasks of multiple applications concurrently. In this paper, we consider the problem of task allocation in software-defined WSNs (SD-WSNs), which are distinguished by centralized control plane and programmable data plane. We extend our previous work on this topic, where we proposed the control algorithm which determines suitability of a sensor node for task allocation based on the active routing paths and residual energy in the network. Availability of such information can be easily justified in SD-WSNs. Through extensive simulations, the performance of this strategy has been evaluated and compared with two conventional task allocation approaches, which assume traditional minimum-hop routing. In addition, we analysed performance of more simple software defined networking-based approach, which performs resource allocation by considering only residual energy in the network. The obtained results demonstrate benefits of SD-WSN architecture when it comes to virtualization efficiency, and clarify improvements achieved by mutual correlation of routing and task allocation decisions.     

基于可靠性的5G网络切片在线映射算法

为了满足业务多样性对5G网络切片带来差异化需求的同时保证切片的可靠性,实现网络资源的优化配置。该文针对5G网络切片的动态映射、轻量级可靠映射问题,提出对计算资源、链路资源和RRU频谱资源联合分配方案。首先,该方案建立面向可靠性约束的多目标资源分配模型,引入李雅普诺夫优化模型,在保证队列稳定同时优化资源分配。其次,提出了基于队列稳定性的虚拟节点映射算法和基于可靠性的虚拟链路映射算法。最后,将时间离散为一系列连续的时间窗,利用时间窗动态处理到达的网络切片请求,实现在线的网络切片映射算法。仿真结果表明,该算法提高了资源利用率,并且保证网络可靠性。     

车联网中网络切片资源分配方案

为了满足车联网中不同应用的服务质量(Quality of Service, QoS)要求,提出了一种基于网络切片技术的车联网频谱资源分配方案。该方案考虑数据接入控制,通过联合优化频谱资源块(Resource Block, RB)分配和车辆信号发射功率控制,在安全服务切片低时延高可靠性的约束下,最大化信息娱乐服务切片的平均和吞吐量。将车联网资源管理建模为一个混合整数随机优化问题,利用李雅普诺夫(Lyapunov)优化理论将该优化问题分解为接入控制和RB分配与功率控制两个子问题,并分别对其进行求解,得到每个时隙的接入控制和资源分配方案。仿真结果表明,所提出的资源分配方案能够有效提高信息娱乐服务切片的平均和吞吐量,并且可以通过调整引入的控制参数值来实现吞吐量和时延的动态平衡。同时,与已有方案相比,该方案具有更好的时延性能。     

An adaptive heuristic algorithm to solve the network slicing resource management problem

Artificial intelligence-based (AI-based) network slicing bandwidth allocation enables the 5G/6G service providers to create multiple virtual networks atop a shared physical infrastructure while fulfilling varying end-user demands. Some researchers argue that AI-enable network may run the danger of having private information compromised. We still need a backup rule-based methodology to allocate bandwidth resource to each slice, if the AI-based method suddenly encounters security issues. To design such a rule-based methodology, this study attempts to answer two questions: (1) Is the network slicing bandwidth allocation problem the nondeterministic polynomial-time completeness (NP-completeness)? (2) Is there a heuristic methodology without any training process, which has equivalent performance compared to the AI-based methodology? This study first proves the classical network slicing bandwidth allocation problems is NP-completeness. This shows that the designed heuristic method is inescapably suboptimal to the network slicing bandwidth allocation problem. Secondly, this study proposes the Adaptive Hungarian Algorithm (AHA), which outperforms previous AI-empowered method and does not need any training process. The experiments demonstrate that AHA reached 93%–97% of the maximal system throughput by brute-and-force algorithm, compared to other methodologies only having at most 93% of the maximal system throughput. This also indicates that AHA is capable to solve the network slicing bandwidth allocation problem, if the telecommunication operators do not have sufficient sample complexity to train an AI model.     

基于预测的5G网络切片算法

5G网络实时应用场景对网络切片的建立提出了严格的要求,需要使用预测算法提前隔离资源,降低网络切片的建立时间。提出了基于预测的 5G 网络切片算法,以四阶矩为代价函数,在算法复杂度不高的前提下提供必要的预测精度,根据预测结果在5G网络中提前隔离虚拟节点资源和虚拟链路资源,当网络切片请求到达时,直接拉起容器,完成网络切片的动态创建。仿真结果表明,所提算法的预测精度能够达到 90%,在复用原始网络切片资源的条件下,新请求网络切片的创建时间减少50%。