DNN-Based Channel Estimation for Nonlinear Impairments-Aware RMSA Algorithm

Study and Analysis of Routing and Spectrum Allocation (RSA) and Routing, Modulation and Spectrum Allocation (RMSA) Algorithms in Elastic Optical Networks (EONs)

This paper focus on the routing, modulation level and spectrum allocation (RMLSA) problem in the next generation datacentre networks, which own the advantages of both Elastic Optical Networks (EON) and Software Defined Networking (SDN). We proposes an Integer Linear Programming (ILP) model for this problem. Simulation results show the ILP model achieves an outstanding load balancing performance.

A non-backtracking spectrum allocation algorithm in a large [formula omitted] under dynamic traffic grooming

This paper focuses on the Routing and Spectrum Allocation (RSA) problem in Coherent Optical Orthogonal Frequency Division Multiplexing (CO-OFDM) Elastic Optical Networks (EON) with consideration of transmission impairments. A majority of the literature in EON is based on improving the spectral efficiency and efficient utilization of available spectral resources. However, transmission impairments such as pass-band filter narrowing effect, shot noise and amplified spontaneous emission (ASE) beat noise products due to coherent detection and cross-talk in cross-connect (XC) etc. limit the unconstrained allocation of spectral resources. Thus, these transmission impairments may eventually become a barrier to the continuous resource allocation in EON. In this paper, we introduce a novel RSA technique with the transmission impairments in the coherent optical transport network, which we formulate as Transmission Impairments Aware RSA (TIA-RSA) problem. First, an optimal integer linear programming (ILP) for RSA is presented which minimizes delay-bandwidth product. Thereafter, a heuristic algorithm for large networks is also proposed. Our results indicate that the proposed heuristic algorithm yields close to optimal solution for low running times. We further propose an architecture for optical XC for EON.

To fully utilize the existing optical network resource, the dynamic traffic grooming technology, which could efficiently multiplex many low-speed services arriving dynamically onto high-capacity optical channels, has been studied extensively and used widely. In this article, the problem of dynamic traffic grooming in joint optimization of IP over elastic optical network (EON) is studied. This problem consists of three sub-problems at two layers: the routing problem at the IP-layer (IPR), the routing, modulation level (RML), and the spectrum allocation (SA) problems at the optical layers. We proposed a novel topology-integration and adaptive-modulation based in cross-layer routing spectrum allocation (CL-RSA) algorithm, which follows a multi-cost approach that solves the IPR, the RML, and the SA problems jointly. The most important features of the proposed algorithm are merging physical topology with virtual topology and using the minimum-weight preferred method for route selection. Meanwhile, the effect of physical-layer impairments (PLI) on signal transmission is considered. In addition, the adaptive modulation scheme is used to allocate the spectrum resource. The simulation results show that the algorithm can effectively improve the spectrum resource utilization and reduce the network blocking probability compared to other algorithms in various network conditions, especially in the high load condition effectively.

Elastic optical network (EON) is considered as the platform for future optical transport networks. Routing and spectrum allocation (RSA) has a significant bearing on EON. Currently, researches tend to presume that RSA supports discrete or continuous rates. However, the approach of applying continues rates inevitably places a high burden on the management and implementation of EON. Contrastingly, discrete rates are static and could be misaligned with the demands of customers. We propose an EON that advertise continuous (any) rates, while in reality admitting a limited set of quantized levels. This approach redesigns the marketing strategy of EON services. We show how to quantize and map the continuous advertised rates into a limited set of quantized levels optimally, and with minimal effect. We use simulation to evaluate the different parameters impacting the continuous model and confirm the feasibility of the proposed model.

Elastic optical networks (EONs) have provision long transmission reach (TR) and high spectral-efficiency (SE). Hence, compared to fixed-grid optical networks, in EONs, managing resources and addressing network design poses complex challenges. In this work, we formulate a link-based mixed integer linear program (MILP) model which considers quality of transmission (QoT) while determining the route, modulation format/level (MF/ML) and spectrum allocation (SA) for every request. To improve SE, model chooses the highest ML; however, when QoT is considered, TR of path with highest ML is very limited. Hence, model finds trade-off between ML, number of required frequency slots (FSs), and TR, with the objective of minimising required amount of network FSs so as to admit all requests. Finally, we evaluate and analyse model's performance and show that for simplicity, existing schemes impractically assume single MF (i.e., higher SE and ML) compared to fixed-grid networks, thereby ignoring the flexible nature of EONs.

Recent advances in physical layer optics have made slicing of optical bands into multiple subbands with different bandwidths possible. Due to this development, spectrum allocation has become easier in elastic optical networks (EONs). More specifically, owing to the slicing technology, the defragmentation problem in EONs can be addressed easily, i.e., more demands can be fit into empty spectrum slots by breaking the demands as needed using the slicing technology. This paper proposes a spectrum allocation scheme considering the slicing process at any nodes, e.g., source node and intermediate nodes, in EONs. Slicing-and-stitching technology is applied to break the contiguous-spectrum constraint in an EON so that spectrum fragmentation is reduced. While slicing a demand from one node to another, the following questions must be answered: (1) Which parts of the spectrum band should be sliced? (2) In which node(s) along the path of a demand should the slicings be done to reduce the bandwidth blocking rate? To answer the above questions, we formulate a mixed-integer linear programming (MILP) model that jointly addresses the above questions as well as minimizes the total number of slicers in a network. To measure the performance of the MILP, we used the bandwidth blocking ratio (BBR) of the network as a performance metric. Our results from the MILP show that introducing slicing at every node in the network improves the BBR by as much as 68% compared to a conventional case where slicing a demand is allowed only at the source node.

This chapter presents the flexible and scalable optical transport network architecture called elastic optical network (EON). To meet future Internet traffic requirements, a novel EON architecture with flexible data rate and spectrum allocation, high resource efficiency, and low power consumption is required. The chapter describes a few of the coherent modulation schemes and the multi‐carrier modulation (MCM) schemes used in EON for better utilization of spectrum and adaptability. It focuses on the coherent optical orthogonal frequency‐division multiplexing MCM scheme as orthogonal frequency division multiplexing has emerged as a leading modulation technique in the broadband radio frequency wireless and in the optical domain as well. To make the EON flexible, several network elements with requisite flexibility are required for generation, switching, and routing of the lightpaths. The chapter discusses these elements in brief. It also gives the routing and spectrum assignment algorithms used in these networks, and explains requirements of network management and control in EONs.

Penalty-method based impairment-aware performance of Elastic Optical Networks with spectrum conversion

Elastic optical networks (EONs) can make service accommodation more flexible and precise by employing efficient routing and spectrum allocation (RSA) algorithms. In order to improve the efficiency of RSA algorithms, the advanced-reservation technique was introduced into designing RSA algorithms. However, few of these advanced-reservation-based RSA algorithms were focused on the unavailable spectrum resources in EONs. In this paper, we propose an Advanced-Reservation-based Invalid-Spectrum-Aware (AR-ISA) resource allocation algorithm to improve the networking performance and the resource alignment of EONs. By employing a new index, Invalid Spectrum Rate (ISR), to record the proportion of unavailable spectrum resources in EONs, the proposed AR-ISA algorithm set a network load threshold to trigger the postponement of an arriving service. Compared with the traditional slack-based AR mechanism, the proposed algorithm has more concerns about the current spectrum usage of the path designated by the service than the conflicts between AR services and other existing services. To further increase the networking performance, the proposed algorithm adopts defragmentation to increase the number of available spectrum resources when postponing a service. Theoretical analysis and simulation results show that the proposed AR-ISA algorithm has obvious effectiveness in reducing the service blocking rate and increasing the spectrum alignment rate.

Spectrum Expansion/Contraction and Survivable Routing and Spectrum Assignment problems on EONs with time-varying traffic

With the growing popularity of 5G mobile communications, cloud and fog computing, 4K video streaming, etc., population distribution and migration have increasing influence on traffic distribution in metro elastic optical networks (EONs). Traffic distribution is further diversified according to people's tendency to use network services in different places at different times. We use the term "tidal traffic" to represent traffic distribution with strong disequilibrium in the time and space dimensions. Note that tidal traffic can potentially result in low bandwidth utilization and weak service capability, as network resources are not allocated properly. To address this problem, in this study, we first analyze traffic characteristics of access networks and metro networks, and mathematically formulate an onion tidal traffic model (OTTM) in EONs. Second, based on the traditional routing and spectrum allocation (RSA) algorithm, which provides end-to-end connection by allocating frequency slot resources in EONs, we propose two algorithms to enhance bandwidth efficiency based on the OTTM model. We call them pre-detour RSA (PD-RSA) and pre-detour k-shortest paths RSA (PDK-RSA). Next, we analyze the shortcomings of a benchmark algorithm named min-hop k-shortest paths RSA (MHK-RSA) under tidal traffic, and compare PD-RSA and PDK-RSA with MHK-RSA via simulation. Simulation results show that PD-RSA and PDK-RSA can effectively reduce at least 26% and 18% of blocking probability, respectively, compared to MHK-RSA with the same time complexity.

Fragmentation-aware algorithms for multipath routing and spectrum assignment in elastic optical networks

Recently, space-division multiplexing (SDM) has been incorporated with elastic optical networks (EONs) to enhance the fiber capability, which forms space-division multiplexing-based elastic optical networks (SDM-EONs). During transmission of optical signals through multi-core fibers, inter-core crosstalk (XT) and intra-core physical layer impairments (PLIs) arise, which deteriorate the signal quality. Existing models typically handle inter-core XT and intra-core PLIs separately and set a single XT threshold for each modulation format, which results in an unacceptable lightpath due to the degradation of signal quality or leads to inefficient spectrum utilization. This paper proposes a routing, modulation, spectrum, and core allocation (RMSCA) model for SDM-EONs to consider inter-core XT and intra-core PLIs jointly. For each modulation format, it sets different XT thresholds and transmission reaches according to inter-core XT and intra-core PLIs. An optimization problem is formulated as an integer linear programming (ILP) problem. We prove that the RMSCA decision problem is NP-complete. We introduce a heuristic algorithm when the ILP problem is not tractable. Numerical results demonstrate that, by setting several XT limits for each modulation format, the proposed model increases spectrum efficiency compared to a benchmark model based on the literature.