Anycast Transmission in Routing Modulation Level Spectrum Assignment (RMLSA) Problem on Space Division Multiplexing (SDM) Elastic Optical Networks (EON)

With the rise of cloud computing in recent years, a large number of streaming media has yielded an exponential growth in network traffic. With the now present 5G and future 6G, the development of the Internet of Things (IoT), social networks, video on demand, and mobile multimedia platforms, the backbone network is bound to bear more traffic. The transmission capacity of Single Core Fiber (SCFs) may be limited in the future and Spatial Division Multiplexing (SDM) leveraging multi-core fibers promises to be one of the solutions for the future. Currently, Elastic optical networks (EONs) with multi-core fibers (MCFs) are a kind of SDM-enabled EONs (SDM-EON) used to enhance the capacity of transmission. The resource assignment in MCFs, however, will be subject to Inter-Core Crosstalk (IC-XT), hence, reducing the effectiveness of transmission. This research highlights the routing, modulation level, and spectrum assignment (RMLSA) problems with anycast traffic mode in SDM-EON. A multipath routing scheme is used to reduce the blocking rate of anycast traffic in SDM-EON with the limit of inter-core crosstalk. Hence, an integer linear programming (ILP) problem is formulated and a heuristic algorithm is proposed. Two core-assignment strategies: First-Fit (FF) and Random-Fit (RF) are used and their performance is evaluated through simulations. The simulation results show that the multipath routing method is better than the single-path routing method in terms of blocking ratio and spectrum utilization ratio. Moreover, the FF is better than the RF in low traffic load in terms of blocking ratio (BR), and the opposite in high traffic load. The FF is better than the RF in terms of a spectrum utilization ratio. In an anycast protection problem, the proposed algorithm has a lower BR than previous works.

Multi-Core Virtual Concatenation Scheme Considering Inter-Core Crosstalk in Spatial Division Multiplexing Enabled Elastic Optical Networks

Spatial division multiplexing enabled elastic optical networks(SDM-EONs) are the potential implementation form of future optical transport networks, because it can curve the physical limitation of achievable transmission capacity in single-mode fiber and single-core fiber. However, spectrum fragmentation issue becomes more serious in SDM-EONs compared with simple elastic optical networks(EONs) with single mode fiber or single core fiber. In this paper, multicore virtual concatenation(MCVC) scheme is first proposed considering inter-core crosstalk to solve the spectrum fragmentation issue in SDM-EONs. Simulation results show that the proposed MCVC scheme can achieve better performance compared with the baseline scheme, i.e., single-core virtual concatenation(SCVC) scheme, in terms of blocking probability and spectrum utilization.

Cost-Minimized Virtual Elastic Optical Network Provisioning with Guaranteed QoS

Network virtualization is important for elastic optical networks(EONs)because of more flexible service provisioning.To ensure guaranteed quality of service(QoS)for each virtual elastic optical network(VEON),clients usually request network resources from a network operator based on their bandwidth requirements predicted from historical traffic demands.However,this may not be efficient as the actual traffic demands of users always fluctuate.To tackle this,we propose a new VEON service provisioning scheme,called SATP,which consists of three stages,i.e.,spectrum assignment(SA),spectrum trading(ST),and spectrum purchasing(SP).Unlike conventional once-for-all VEON service provisioning approaches,the SATP scheme first allocates spectrum resources to VEONs according to their predicted bandwidth requirements with a satisfaction ratio α(0<α≤1).Then,to minimize service degradation on VEONs which are short of assigned spectra for their peak traffic periods,the scheme allows VEONs to trade spectra with each other according to their actual bandwidth requirements.Finally,it allows VEON clients to purchase extra spectrum resources from a network operator if the spectrum resources are still insufficient.To optimize this entire process,we formulate the problem as a mixed integer linear programming(MILP)model and also develop efficient heuristic algorithms for each stage to handle large test scenarios.Simulations are conducted under different test conditions for both static and dynamic traffic demand scenarios.Results show that the proposed SATP scheme is efficient and can achieve significant performance improvement under both static and dynamic scenarios.

Resource Allocation Using SPA Based on Different Cost Functions in Elastic Optical Networks

Routing, modulation and spectrum allocation in elastic optical networks is a problem aiming at increasing the capacity of the network. Many algorithms such as shortest path algorithm can be used as the routing section of this problem. The efficiency of these algorithms is partly based on how the cost of each link is defined. In this study, we considered several basic metrics in cost of network links and compared their effects on the network capacity. In particular, the static costs and the dynamic costs were evaluated and compared. For dynamic scenarios, compared to static scenarios, at least one additional factor, the usage of the links, was added. We further considered a new factor that is based on probability of accommodating the signal at a given time in any given link. The results show that, among them, the shortest path algorithm provides the least blocking probability when the cost is a combination of link length and the abovementioned possibility/usage of the link.

Elastic Resource Allocation for Multi-Granularity Multicasting Traffic in OFDM-Based Optical Networks

With the increasing requirements of the multicast services in the whole data traffic service, the optical multicast technology becomes a key technology supporting wide bandwidth and high speed multicasting communication. The transmission efficiency, capacity and robustness of optical multicast network can be further improved by introducing network coding technology into optical multicast networks. Meanwhile, facing to demand of emerging rate-variable multi-granularity multicast service, a multi-path transmission scheme based on network coding for routing and spectrum allocation (RSA) is proposed. It can not only allocate spectrum resources effectively and flexibly for various-rate multicast traffic, but also balance the network load, improve network throughput and reduce transmission blocking rate. In this paper, RSA problem is decomposed into two subproblems, namely routing allocation based on network coding and spectrum allocation based on maximum spectrum first (MSF) strategy, which are solved sequentially. Simulation experiments are carried out to analyze transmission performance with proposed RSA scheme. The simulation results show that the proposed RSA mechanism can allocate spectrum resources efficiently and flexibly for multi-granularity multicast traffic. Compared with RSA schemes based on shortest path tree (SPT) and minimal spanning tree (MST), the proposed RSA scheme is more efficient for spectrum resource utilization and load balancing, and spectrum resource is saved more than 20%.

Minimizing Traffic Blocking and Inter-Crosstalk in Spatial Division Multiplexing over Elastic Optical Networking

As a promising solution, virtualization is vigorously developed to eliminate the ossification of traditional Internet infrastructure and enhance the flexibility in sharing the substrate network (SN) resources including computing, storage, bandwidth, etc. With network virtualization, cloud service providers can utilize the shared substrate resources to provision virtual networks (VNs) and facilitate a wide and diverse range of applications. As more and more internet applications migrate to the cloud, the resource efficiency and the survivability of VNs, such as single link failure or large-scale disaster survivability, have become crucial issues. Elastic optical networks have emerged in recent years as a strategy for dealing with the divergence of network application bandwidth needs. The network capacity has been constrained due to the usage of only two multiplexing dimensions. As transmission rates rise, so does the demand for network failure protection. Due to their end-to-end solutions, those safe-guarding paths are of particular importance among the protection methods. Due to their end-to-end solutions, those safeguarding paths are of particular importance among the protection methods. This paper presents approaches that provide a failure-independent route-protecting p-cycle for path protection in space-division multiplexed elastic optical networks. This letter looks at two SDM network challenges and presents a heuristic technique (k-shortest path) for each. In the first approach, we study a virtual network embedding (SVNE) problem and propose an algorithm for EONs, which can combat against single-link failures. We evaluate the proposed POPETA algorithm and compare its performance with some counterpart algorithms. Simulation results demonstrate that the proposed algorithm can achieve satisfactory performance in terms of spectrum utilization and blocking ratio, even if with a higher backup redundancy ratio.

Hybrid Policy of Routing and Spectrum Assignment in Elastic Optical Networks

The major challenge in elastic optical networks is to determine the path of a connection and to allocate spectral resources on the links of this path. This problem consists of two sub-problems, routing and spectrum allocation. In the literature, these sub-problems are solved with a predefined order for all topology node pairs. Recent work proposes hybrid resolution algorithms based on connection demand and network state to provide a solution to these problems. However, the blocking rate of new connection requests has become problematic. In this work, we propose a hybrid routing and spectrum assignment policy to improve blocking rate of new connection requests. The proposed solution consists to change the routing policy of a pair node if the connection request is blocked. This algorithm improves the blocking rate of new connection requests.

Edge computing oriented virtual optical network mapping scheme based on fragmentation prediction

As edge computing services soar,the problem of resource fragmentation situation is greatly worsened in elastic optical networks(EON).Aimed to solve this problem,this article proposes the fragmentation prediction model that makes full use of the gate recurrent unit(GRU)algorithm.Based on the fragmentation prediction model,one virtual optical network mapping scheme is presented for edge computing driven EON.With the minimum of fragmentation degree all over the whole EON,the virtual network mapping can be successively conducted.Test results show that the proposed approach can reduce blocking rate,and the supporting ability for virtual optical network services is greatly improved.

Resource Optimization in Elastic Optical Networks Using Threshold-Based Routing and Fragmentation-Aware Spectrum Allocation

This paper proposes an efficient strategy for resource utilization in Elastic Optical Networks (EONs) to minimize spectrum fragmentation and reduce connection blocking probability during Routing and Spectrum Allocation (RSA). The proposed method, Dynamic Threshold-Based Routing and Spectrum Allocation with Fragmentation Awareness (DT-RSAF), integrates rerouting and spectrum defragmentation as needed. By leveraging Yen’s shortest path algorithm, DT-RSAF enhances resource utilization while ensuring improved service continuity. A dynamic threshold mechanism enables the algorithm to adapt to varying network conditions, while its fragmentation awareness effectively mitigates spectrum fragmentation. Simulation results on NSFNET and COST 239 topologies demonstrate that DT-RSAF significantly outperforms methods such as K-Shortest Path Routing and Spectrum Allocation (KSP-RSA), Load Balanced and Fragmentation-Aware (LBFA), and the Invasive Weed Optimization-based RSA (IWO-RSA). Under heavy traffic, DT-RSAF reduces the blocking probability by up to 15% and achieves lower Bandwidth Fragmentation Ratios (BFR), ranging from 74% to 75%, compared to 77% - 80% for KSP-RSA, 75% - 77% for LBFA, and approximately 76% for IWO-RSA. DT-RSAF also demonstrated reasonable computation times compared to KSP-RSA, LBFA, and IWO-RSA. On a small-sized network, its computation time was 8710 times faster than that of Integer Linear Programming (ILP) on the same network topology. Additionally, it achieved a similar execution time to LBFA and outperformed IWO-RSA in terms of efficiency. These results highlight DT-RSAF’s capability to maintain large contiguous frequency blocks, making it highly effective for accommodating high-bandwidth requests in EONs while maintaining reasonable execution times.

SDM-EON中基于串扰避免的多纤芯分配算法

为了解决空分复用弹性光网络中的频谱碎片、路由频谱纤芯分配(RSCA)和低业务负载下芯间串扰等问题,建立针对多纤芯RSCA问题的动态业务分割整数线性规划(ILP)模型,提出基于串扰避免的多纤芯分配算法(PS-MCT)。在路由选择阶段,综合路径负载和跳数设计路径排序公式;在频谱分配阶段,将纤芯分组,组内纤芯分类和多纤芯分配相结合;通过业务分割的方式使多个子业务独立地在同组内的多条纤芯上传输,从而减小串扰和碎片的产生。仿真结果表明,与对比算法相比,所提算法在带宽阻塞率和频谱利用率方面都取得了较好的性能。

EON中针对提前预留业务的碎片感知RSA算法

为了减少弹性光网络(EON)中的频谱和时间碎片,针对提前预留(AR)业务提出一种碎片感知路由与频谱分配(RSA)算法。在选路阶段,该算法采用K最短路径算法,综合考虑路径距离、跳数、频谱资源消耗和邻接链路数等因素影响来挑选侯选路径集;在资源分配阶段,则采用局部影响因子统计可能产生的频谱和时间碎片,以降低候选资源块周围的频谱、时间资源碎片化程度,并利用整体影响因子尽可能将占用资源集中在频率轴边界处,以增加中间空闲资源连续性,同时还引入时域资源使用度因子以避免过度占用资源。仿真结果表明,该算法进一步改善了带宽阻塞率性能,提高了资源利用率。

基于深度学习的面向IP-over-EON的可编程跨层网络业务性能感知系统

为了实现实时的、细粒度的网络性能监测与调整,并且满足不同应用的特定服务质量需求,提出了基于深度学习的面向IP-over-EON的可编程跨层网络业务性能感知系统。该系统将基于网络业务性能感知的分布式网络监测与集中式网络管控相结合,分布式网络监测实现跨层和细粒度的网络监控,并基于深度学习进行数据分析。实验结果表明,该系统通过有机地结合集中式与分布式的处理方式,实现了及时的、自动化的网络控制与管理,具有良好的可扩展性。

Reinforced virtual optical network embedding algorithm in EONs for edge computing

As the core technology of optical networks virtualization, virtual optical network embedding(VONE) enables multiple virtual network requests to share substrate elastic optical network(EON) resources simultaneously and hence has been applicated in edge computing scenarios. In this paper, we propose a reinforced virtual optical network embedding(R-VONE) algorithm based on deep reinforcement learning(DRL) to optimize network embedding policies automatically. The network resource attributes are extracted as the environment state for model training, based on which DRL agent can deduce the node embedding probability. Experimental results indicate that R-VONE presents a significant advantage with lower blocking probability and higher resource utilization.

基于孤立森林算法的弹性光网络异常流量自动识别方法

弹性光网络流量传输受到时间波动导致异常,为了提高网络传输稳定性,提出基于孤立森林算法的弹性光网络异常流量自动识别算法。根据流量的异常分布特征和正常数据的差异性进行波谱密度检测,构建弹性光网络流量的谱特征提取模型,通过低通滤波器卷积向量重组,实现对异常流量的谱特征筛选,采用孤立森林算法实现对网络流量异常检测的自适应寻优控制,结合多维空间结构重组方法实现对弹性光网络异常流量检测和识别。结果表明,漏检率及误检率较低,分别为3.16%,1.03%。检测用时较少,仅用16秒。在进行检测时,外部入侵率未超过1%,抗扰性较强。

一种基于串扰污染区域的SDM-EON网络中超级通道构建

空分复用弹性光网络(Space Division Multiplexing Elastic Optical Networks,SDM-EON)技术具有细粒度、高容量、高速率等特性,是未来光传输网络的核心技术,然而,加入了空间维度,网络中超通道的构建更加复杂化。为了有效地构建SDM-EON中超通道,文章首先提出核间串扰污染区域(Crosstalk-contaminated Area,CA)的新概念,描述受到核间串扰的频谱段。基于CA的概念,提出了一种新型的构建超级通道的路由、频谱和核分配(RSCA)算法。仿真结果表明,基于CA的超级通道构建方案(SCCA)比基准算法有更低的阻塞率,能实现更好的性能。

弹性光前传中的功能分割选择与资源分配优化

为了显著提升弹性光前传(EOF)网络的能效,提出了一种EOF中的功能分割选择与资源分配优化方案。该方案通过引入改进的Lyapunov漂移技术,解决了功能分割与资源分配中复杂的时间平均随机优化难题,实现了网络资源的动态高效调配。此外,还深入探讨了天线端口数量扩增与光纤频谱粒度细化对方案性能产生的积极效应。仿真结果表明:相较于传统的基于光前传的云无线接入网(C-RAN),该方案不仅大幅降低了平均功耗,降幅高达70%,而且确保了前传延迟维持在250μs以下,展现了卓越的性能优势。

弹性光网络分层流量疏导优化方法(特邀)

【目的】随着云计算、大数据和数据中心(DC)等技术的迅猛进步,DC的规模与数量正在持续扩张和增长,网络的带宽资源和能耗也在急速增长。如何有效减少网络带宽资源与能耗受到广泛关注。文章旨在减少网络能耗和提高网络频谱资源利用效率。【方法】考虑工作网络能耗元件特点、频谱资源分配方式和不同调制格式选择,文章采用自适应流量疏导方法和频谱分层方式,提出了弹性光网络的距离自适应分层流量疏导方法(DSGM),把频谱资源划分成不同频谱层进行网络流量疏导。一方面,根据距离自适应调制方法选择不同频谱效率的调制格式;另一方面,根据频谱分层流量疏导方式,对每一条光纤的空闲频谱资源按不同速率的光通道进行分层,通过光纤链路剩余带宽资源,来选择合适的光通道进行流量疏导,优化频谱资源的使用。为了方便比较,文章引入了频谱分层流量疏导方法(SSGM)、传统流量疏导方法(TTGM)和没有流量疏导的传统方法(TMWG)。【结果】仿真结果表明,与SSGM、TTGM和TWGM相比,文章所提DSGM能明显降低弹性光网络能耗,减少网络的阻塞率,提高资源利用效率。【结论】通过文章所提弹性光网络分层流量疏导优化方法,实现了网络能耗与频谱资源优化的目标。

基于SDN弹性光网络的电力通信网智能业务编排方法

针对电力通信网差异化业务编排问题,首先构造基于SDN弹性光网络的电力通信网框架,通过业务层与SDN控制层完成配电网数据交互,支撑配网多种不同优先级电力通信网业务的正常运行。其次,提出基于自适应业务优先级感知的电力通信网智能业务编排算法,根据不同业务优先级自适应调节探索因子,权衡不同优先级业务摇臂选择时的探索和利用的倾向,从而保证高优先级业务的高可靠传输的同时降低网络开销。最后,通过算例分析验证所提技术在能效、时延等方面的性能优势。文章的研究内容能为电力通信网差异化业务数据流低时延高效传输提供参考,从而支撑电力通信网高效运行。

基于深度强化学习的C+L波段弹性光网络频谱分配算法

针对C+L波段弹性光网络中受激喇曼散射(SRS)效应导致物理层损伤加剧的问题,提出一种基于深度强化学习(DRL)自适应调制格式的频谱分配算法,在路由阶段,采用K最短路由算法为业务请求预计算K条最短备选路径;在波段、调制格式与频谱分配阶段,采用DRL进行智能化决策,并结合了2种奖励函数,以降低网络阻塞率并提高频谱使用效率。仿真结果表明,该算法能够有效降低阻塞率并提高频谱利用率。