Space-Division Multiplexing in Data Center Networks: On Multi-Core Fiber Solutions and Crosstalk-Suppressed Resource Allocation

The rapid growth of traffic inside data centers caused by the increasing adoption of cloud services necessitates a scalable and cost-efficient networking infrastructure. Space-division multiplexing (SDM) is considered as a promising solution to overcome the optical network capacity crunch and support cost-effective network capacity scaling. Multi-core fiber (MCF) is regarded as the most feasible and efficient way to realize SDM networks, and its deployment inside data centers seems very likely as the issue of inter-core crosstalk (XT) is not severe over short link spans (<1  km ) compared to that in long-haul transmission. However, XT can still have a considerable effect in MCF over short distances, which can limit the transmission reach and in turn the data center’s size. XT can be further reduced by bi-directional transmission of optical signals in adjacent MCF cores. This paper evaluates the benefits of MCF-based SDM solutions in terms of maximizing the capacity and spatial efficiency of data center networks. To this end, we present an analytical model for XT in bi-directional normal step-index and trench-assisted MCFs and propose corresponding XT-aware core prioritization schemes. We further develop XT-aware spectrum resource allocation strategies aimed at relieving the complexity of online XT computation. These strategies divide the available spectrum into disjoint bands and incrementally add them to the pool of accessible resources based on the network conditions. Several combinations of core mapping and spectrum resource allocation algorithms are investigated for eight types of homogeneous MCFs comprising 7–61 cores, three different multiplexing schemes, and three data center network topologies with two traffic scenarios. Extensive simulation results show that combining bi-directional transmission in dense core fibers with tailored resource allocation schemes significantly increases the network capacity. Moreover, a multiplexing scheme that combines SDM and WDM can achieve up to 33 times higher link spatial efficiency and up to 300 times greater capacity compared to a WDM solution

Geographic model for cost estimation of FTTH deployment: overcoming inaccuracy in uneven-populated areas

A geographic approach is proposed to accurately estimate the cost of FTTH networks. In contrast to the existing geometric models, our model can efficiently avoid inaccurate estimation of the fibre infrastructure cost in the uneven-populated areas

Geometric versus geographic models for the estimation of an FTTH deployment

Optical access networks provide a future proof platform for a wide range of services, and today, several operators are deploying fibre to the home (FTTH) networks. Installing an FTTH infrastructure, however, involves very high investment cost. Therefore, a good estimation of the investment cost is important for building a successful business strategy and, consequently, to speed up the FTTH penetration. In this paper, for calculating the amount of cable and fibre in the outside plant together with the associated civil works, and the number of required network elements, two different approaches are investigated: (1) geometric modelling of the fibre plant based on approximate mathematical models and (2) geographic modelling of the fibre plant based on map-based geospatial data. The results obtained from these two approaches can then be used as input for preliminary investment cost calculations and/or techno-economic evaluations. Compared to more complex and accurate geographic modelling, we verify that especially with uneven population density and irregular street system, simple geometric models do not provide accurate results. However, if no geospatial data is available or a fast calculation is desired for a first estimation, geometric models definitely have their relevance. Based on the case studies presented in this paper, we propose some important guidelines to improve the accuracy of the geometric models by eliminating their main distortion factors

Access and metro network convergence for flexible end-to-end network design

This paper reports on the architectural, protocol, physical layer, and integrated testbed demonstrations carried out by the DISCUS FP7 consortium in the area of access - metro network convergence. Our architecture modeling results show the vast potential for cost and power savings that node consolidation can bring. The architecture, however, also recognizes the limits of long-reach transmission for low-latency 5G services and proposes ways to address such shortcomings in future projects. The testbed results, which have been conducted end-to-end, across access - metro and core, and have targeted all the layers of the network from the application down to the physical layer, show the practical feasibility of the concepts proposed in the project

Energy-efficient WDM network planning with dedicated protection resources in sleep mode

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Network performance trade-Off in optical spatial division multiplexing data centers

We propose close-to-optimal network resource allocation algorithms modular data centers using optical spatial-division multiplexing. A trade-off between the number of established connections and throughput is identified and quantified

Limiting physical-layer attack propagation with power equalization placement in transparent WDM networks

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Restoration in optical cloud networks with relocation and services differentiation

©2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.Optical cloud networks allow for the integrated management of both optical and IT resources. In this paradigm, cloud services can be provisioned in an anycast fashion; i.e., only the source node asking for a service is specified, while it is up to the cloud control/management system to select the most suitable destination data center (DC) node. During the cloud service provisioning process, resiliency is crucial in order to guarantee continuous network operations also in the presence of failures. On the one hand, a survivability strategy needs to be able to meet the availability requirements of each specific cloud service, while on the other hand it must be efficient in using backup resources. This paper proposes a restoration-based survivability strategy, which combines the benefits of both cloud service relocation and service differentiation concepts. The former is used to enhance the restorability performance (i.e., the percentage of successfully restored cloud services) offered by restoration, while the latter ensures that critical services are given the proper consideration while backup resources are assigned. The paper proposes both an integer linear programming (ILP) formulation, which guarantees optimal results, and a heuristic, which trades the optimality of the solution achieved by the ILP for faster processing times. Simulation results show that the average service availability and restorability performance obtained by both the ILP and the heuristic are very close to that achievable using a protection-based strategy, but with the inherent benefit, in terms of efficient use of resources, offered by a restoration-based approach.Peer ReviewedPostprint (author's final draft