Piotr Lechowicz

Survey of resource allocation schemes and algorithms in spectrally-spatially flexible optical networking

Space division multiplexing (SDM) is a promising optical network solution with the scaling potential to overcome the possible capacity crunch problem in backbone networks. In SDM optical networks, optical signals are transmitted in parallel through spatial modes co-propagating in suitably designed optical fibers. The combination of SDM with wavelength division multiplexing technologies, based on either fixed or flexible frequency grids, allows for a significant increase in the transmission system capacity and improves network flexibility through the joint management of spectral and spatial resources. The goal of this tutorial paper is to survey the resource allocation schemes and algorithms that aim at efficient and optimized use of transmission resources in spectrally and spatially flexible optical networks. There are several flavors of SDM, which results from available optical fiber and switching technologies; hence, we begin from classifying SDM optical network scenarios. As some SDM solutions have specific limitations, for instance, due to coupling of spatial modes, we discuss related constraints and their impact on resource allocation schemes. Along with defining possible SDM scenarios, we survey the proposed in the literature resource allocation algorithms and classify them according to diverse criteria. This study allows us to overview the state-of-the-art solutions in the scope of planning and operating SDM optical networks in a systematic way as well as to identify some open issues that lack solutions and need to be addressed.

ILP modeling of flexgrid SDM optical networks

Due to continuously increasing popularity of various network services the overall Internet traffic grows quickly. According to the recent Visual Networking Index report published by Cisco, the IP traffic will grow at a compound annual growth rate (CAGR) of 22 percent from 2015 to 2020. Space division multiplexing (SDM) in optical networks seems to be a promising solution with the scaling potential to overcome the possible capacity crunch problem in backbone networks. The key idea behind SDM is to exploit the spatial dimension to provide a significant increase in the transmission system capacity. The simplest version of SDM assumes the use of fiber-bundles composed of physically-independent, single-mode fibers. More advanced SDM deployments are based on multicore fibers (MCF) or multimode fibers (MMF). The main goal of this paper is to present integer linear programming (ILP) optimization models for flexgrid SDM optical networks. The proposed models reflect different ways of realizing SDM transmission, each characterized by different flexibility in the use of spatial and spectral resources. Since detailed ILP models precisely describing technological aspects of SDM may be difficult to solve due to their complexity, we provide an analysis of these issues. Eventually, we complement our study with a brief description of optimization algorithms that might be suitable for SDM optical networks.

Genetic Algorithm for Routing and Spectrum Allocation in Elastic Optical Networks

Elastic Optical Network (EON) architecture has been proposed as a promising technology for a new generation of OFDM networks. It is based on the concept that spectrum can be split into smaller slices than are used currently in the fixed-grid network. It allows better spectral utilization and support for bit rates over 100 Gb/s. EONs arise with the problem of routing and spectrum allocation (RSA). In this paper, we propose a Genetic Algorithm (GA) to solve the RSA problem with multicast flows. Different selection and crossover strategies are presented. Extensive numerical experiments are performed to select the most appropriate combination of operators and tuning parameters of the GA algorithm in the context of the RSA problem. Obtained results show that GA can be applicable.

Spectrum usage for various SDM scenarios

Space division multiplexing (SDM) seems to be a promising solution with the scaling potential to overcome the possible capacity crunch problem in optical backbone networks. The main goal of this paper is to provide a detailed analysis of three SDM scenarios, namely, SDM-Fixed, SDM-Single, and SDM-Flexible in terms of the spectrum usage and the wastage of spectral resources due to guardbands and resource overprovisioning.

Greedy randomized adaptive search procedure for joint optimization of unicast and anycast traffic in spectrally-spatially flexible optical networks

Abstract The volume of data traffic in backbone networks is increasing at a speed that exceeds the growth rates of capacities offered in currently used wavelength division multiplexing (WDM) networks. As a short term solution to the potential capacity crunch, the concept of flexible-grid elastic optical networks is nowadays implemented in many backbone networks. However, in a longer term the space division multiplexing (SDM) technology is the most promising solution for satisfying the capacity requirements in future optical networks. The combination of both technologies allows for realization of spectrally-spatially flexible optical networks (SS-FONs). In this paper, we focus on a network scenario in which two different types of traffic flows are carried over an SS-FON, namely, unicast and anycast flows. Unicast flows are used for basic one-to-one communication, while anycast flows — defined as one-to-one-of-many communication — are related to the network traffic generated in data centers and the fact that data centers placed in different network locations can provide the same service or content to network users. For provisioning of lightpaths for both types of traffic, we address the basic optimization problem in SS-FONs, which is routing, space and spectrum allocation (RSSA). The aim of this study is threefold. First, we propose an effective metaheuristic method based on the greedy randomized adaptive search procedure (GRASP) to solve the RSSA problem. Second, we compare performance of the proposed GRASP method against reference optimization approaches. Finally, we present and discuss a wide range of experiments focused on analysis of SS-FONs with joint unicast and anycast traffic. The main conclusions are: (i) the proposed GRASP algorithm provides results very close to optimal (only 0.5% optimality gap) for smaller problem instances and significantly outperforms other heuristics for larger problem instances (in average around 6.8% better than the reference simulated annealing algorithm); (ii) the use of anycast connections in SS-FONs allows to improve the network performance in terms of spectrum usage.

Influence of modulation format transmission reach on performance of elastic optical networks

Flexible-grid elastic optical networks (EONs) are expected to substitute in near future fixed-grid wavelength division multiplexing (WDM) optical networks. The previous works that were focused on optimization of EONs take many different assumptions regarding the transmission reach of modulation formats (MFs). However, according to the best of our knowledge, there have been no comparative analysis showing how the transmission reach models impact the network performance in terms of both spectrum and transceiver usage. In this paper, we address joint optimization of these two key resources in EONs. The main contribution of this work is a detailed analysis of the MF transmission reach impact on the spectrum consumption and transceiver usage in EONs. We present and discuss results of extensive numerical experiments run on representative network topologies with realistic physical assumptions considering various transmission reach values of the applied MFs.

Column generation technique for optimization of survivable flex-grid SDM networks

In this paper, we address the problem of routing, space and spectrum assignment (RSSA) in survivable flex-grid networks that implement spatial division multiplexing (SDM). In our consideration, we focus on two switching policies for the SDM (namely, independent and joint) while the network survivability is provided by dedicated path protection (DPP). We formulate the problem (RSSA-DPP) as an integer linear programming (ILP) and we provide two solution algorithms including column generation (CG)-based method. Then, we perform simulations focused on the evaluation of the CG performance and analysis of the spectrum usage in survivable and flex-grid SDM networks. The results show that the proposed CG is a promising approach that outperforms reference heuristic. The CG method works especially efficiently for joint switching policy (average gap to optimal result was at most 2.2%). Moreover, the results show that SDM architecture can provide significant spectrum savings whose amount depends mostly on the applied switching policy.

Path optimization in 3D printer: Algorithms and experimentation system

3d Printers create an object by printing thousands of successive thin layers. Each layer is created by the printing tool which moves on the selected paths. The ability to reduce the total length of printing paths results in lower overall time needed for printing process. In this paper there are presented two hybrid algorithms for that purpose, Greedy Two Opt and Greedy Annealing. Both of them based on the same assumption that it is profitable to select initial solution with fast algorithm and after that, to try to improve it by further exploration of the solution space with the other one. The simulations made with the designed experimentation system confirmed good properties of the implemented algorithms.