Maximum Entropy (MaxEnt) Routing and Spectrum Assignment for Flexgrid-based Elastic Optical Networking

Presents corrections to the paper, “Multicast routing and distance-adaptive spectrum allocation in elastic optical networks with shared protection,” (Cai, A., et al), J. Lightw. Technol., vol. 34, no. 17, pp. 4076–4088, Sep. 2016.

The routing and spectrum assignment problems in elastic optical networks are well-known NP-hard problem, and are even more complex and challenging when the energy consumption is taken into account. To tackle this challenging problem, we establish a bi-level programming model with the energy consumption of the optical networks and the maximum index of used frequency slots as the leader’s and follower’s objectives to be minimized, respectively, which are used to determine the optimal schemes of routing and spectrum assignments. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. We use heuristic algorithm to sort the connection requests and design a genetic algorithm with tailor-made crossover, mutation and local search operator to look for an optimal routing and spectrum assignment scheme. Finally, simulation experiments are conducted, and the experimental results indicate the effectiveness of the proposed model and algorithms.

A brief review of protection based routing and spectrum assignment in elastic optical networks and a novel p-cycle based protection approach for multicast traffic demands

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

We propose and investigate a subtree scheme for all-optical multicast routing, modulation level and spectrum allocation (AOM-RMSA) in elastic optical networks. A multicast request is accommodated by several light-trees and each light-tree covers only a part of the destination set. We assume that all nodes are multicast capable and investigate the subtree scheme over the single light-tree scheme for the AOM-RMSA problem under both static and dynamic traffic scenarios. In the static scenario, we formulate an integer linear programming model to obtain the optimal solution. Then, we propose two time-efficient heuristic algorithms that construct subtrees according to the link-sharing ratio between the paths from source to two distinct destinations. The proposed algorithms improve the spectrum utilization by building subtrees that have smaller tree-spanning size and adopt higher level modulation formats. They have also effectively reduced the blocking probability compared to single light-tree schemes.

A neural net algorithm for multidimensional maximum entropy spectrum estimation

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.

Objectives: The current technologies of wavelength routing and allocation of available for WDM networks are no longer applicable in Elastic Optical Networks (EON), since all their connections are allocated in a fixed manner, as provided for ITU. Therefore, the topic concerning routing and allocation of resources in EON is relevant given the growth projected in web traffic. This survey includes the evolution, main characteristics, and the process of routing and allocation of wavelengths required by EON. Methodology: The processes of allocation of sub-wavelengths and those of super-wavelengths are presented, as well as the multiple storage for different transmission rates and the principle of spectral contiguity. The process of routing and allocation taking OFMD into account is explained. Findings: In this study, we present a survey with routing and allocation techniques of wavelengths that improve the spectral efficiency of EON. Application/Improvements: This survey provides a wide knowledge on the methods to improve the spectral efficiency in EON. Such efficiency can promote an advance in new routing and allocation techniques for the optical transport networks. Keywords: Elastic Optical Networks, EON, Optical Networks, Routing, WDM

This paper considers distance adaptive dynamic routing and spectrum assignment (RSA) for elastic optical networks with shared backup path protection (SBPP). Efficient heuristic algorithms based on spectrum window planes are proposed for implementing distance and modulation format adaptive RSA so as to maximize spare capacity sharing among multiple protection lightpaths. A differentiated sharable frequency slot cost was also defined for the first time to more efficiently share protection resource. Network performance is evaluated in terms of bandwidth blocking probability (BBP) through simulations. The proposed SBPP technique is effective in reducing BBP and improving spectral efficiency compared to conventional SBPP schemes and 1+1 path protection. The impact of transponder tunability on bandwidth blocking performance is also evaluated to show that a limited tuning range is sufficient to achieve a BBP performance close to that with full tunability.

We consider an elastic all-optical network, where each node is multicast-capable and does not support spectrum conversion. In such a network, for a given set of static multicast demands, we consider distance-adaptive spectrum resource allocation, and aim to optimize multicast routing, modulation, and spectrum assignment with shared protection in a way that minimizes the required spectrum resources for accommodating all multicast sessions. In our design, we provision each multicast demand by a light-tree where spectrum resources are allocated in all links included in the tree. We protect each light-tree from any single link failure in both directions by having a backup path that is link-disjoint to the path from the source to each destination on the primary tree. We reserve spectrum resources in the links that are not in the primary tree but in the backup paths between all source-destination pairs. The reserved spectrum resources can be shared to protect multiple light-trees as long as they do not fail simultaneously. For such a problem, we provide a mixed integer linear programming formulation. We also develop a scalable heuristic algorithm with an attribute that enables it to improve the quality of the results at the cost of longer running times. Numerical results for small problems show that the heuristic algorithm performs close to the optimum. In addition, we use a Markov chain simulation of the network to evaluate the performance of our proposed algorithm in terms of blocking probability in a dynamic environment, which demonstrates a significant improvement over straightforward approaches.

Deep reinforcement learning (DRL) has been introduced to the routing and spectrum assignment (RSA) of elastic optical networks (EONs) where the RSA policies are learnt during the interaction of a DRL agent with the EON environment. Upon each new traffic arrival, the DRL agent senses the EON state, and makes the RSA decision accordingly. Therefore, the EON state feature extraction is essential for the performance. However, current approaches, mainly based on fully connected neural networks or convolutional neural networks, are unsatisfactory in EON state feature extraction due to the following two reasons. (1) The optical network topology information is not well considered. (2) The path-level features are highly related to the RSA decision, due to the spectrum continuity constraint, while path-level feature extraction has not been well exploited. To overcome the above shortcomings, in this paper, we propose to utilize the Graph Convolutional Neural Network (GCN) and the Recurrent Neural Network (RNN) for the feature extraction of the network topology, and the aggregation of link-level features to path-level features. By doing this, critical RSA-related information can be sensed by the DRL agent to make better actions. Simulation results demonstrate that our proposed method outperforms previous approaches.

Extending light-trail into elastic optical networks for dynamic traffic grooming

An elastic optical network (EON) plays an important role in transport technology for virtualization of networks. A key aspect of EONs is to establish lightpaths (virtual links) with exactly the amount of spectrum that is needed and with the possibility of grooming, the process of grouping many small traffic flows into larger units, creating a super-lightpath. Grooming eliminates the need for many guard bands between lightpaths and also saves transceivers; however, it often leads to the need to perform optical–electrical–optical conversions to multiple-data-rate optical signals at intermediate nodes. The aim of this paper is to provide a mixed-integer linear programming (MILP) formulation, as well as heuristic and meta-heuristic approaches, for the design of multiple virtual optical networks (VONs) in an elastic optical substrate network with bandwidth-variable lightpaths, modulation format constraints, and virtual elastic regenerator placement. Traffic grooming is allowed inside each VON, and a distance-adaptive modulation format technique is employed to guarantee efficiency in terms of bandwidth for a physical substrate, subject to several virtual topologies. A reduced MILP formulation without grooming capability is also proposed for comparison. The complete MILP formulation jointly solves the virtual topology design, regenerator placement, and grooming problems, as well as the routing, modulation, and spectrum assignment (RMSA) problem. The reduced MILP formulation, heuristics, and meta-heuristic, on the other hand, separate the virtual topology design problem from the RMSA problem. It is shown that the grooming approach can provide good results, since it solves the problem for a complete design when compared to the approach without grooming. Furthermore, heuristic solutions for large networks are proposed, which present good performance (in terms of saving spectrum) for the design with large instances.

Power, routing, Modulation Level and Spectrum Assignment in all-optical and elastic networks

This paper proposes light trail-based algorithms for routing and resource allocation in Hybrid Networks. In hybrid networks Elastic Optical Network is back end while WiMAX complements as access network. Various network configurations coupled with different permutations of source–destination pairs are used for simulations. Algorithms proposed here found to perform better in terms of bandwidth blocking ratio in all the given networks coupled with minimum network resource utilization.