A constrained-lower-indexed-block spectrum assignment policy in elastic optical networks

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

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

Elastic Optical Networks has drawn a lot of attention in the past few years because of its ability to transmit different data rates increasing or decreasing the optical spectrum according to the necessary demand, ensuring a high spectral efficiency. However, establishing and tearing down different connections ends up segmenting the spectrum in several small fragments, making it impossible for new requests to be attended. Besides, another recurrent problem in elastic optical networks, called routing and spectrum assignment (RSA), aims to find a path and assign to it a contiguous number of spectrum slots using the smallest possible amount of spectral resources. The main purpose of this paper is to propose an algorithm to minimize the spectrum fragmentation problem in Elastic Optical Networks by using RSA algorithms. Results obtained through simulations indicates that the proposed algorithm outperforms in terms of blocking probability and spectrum fragmentation ratio the other existing ones.

Routing and Spectrum Assignment is a key issue in Elastic Optical Networks (EON). Under dynamic traffic conditions, spectrum fragmentation of the frequency resources reduces the spectrum utilization efficiency, and hence degrades the service blocking probability. To address this problem, this paper proposes an improved fragmentation aware routing and spectrum assignment algorithm (FA-RSA) for EON by considering the spectrum fragmentation in the routing decision and spectrum allocation phase. Theoretical analysis and numerical simulation results show that compared with the traditional Random-Fit (RF) and First-Fit (FF) algorithm, the improved algorithm can significantly reduce the blocking probability and improve spectrum utilization.

Recently proposed Elastic Optical Networks (EON) provide optimized bandwidth utilization through a better fitting match between connection bandwidth requirements and spectrum occupation. In an EON, lightpaths are established using a Routing and Spectrum Assignment (RSA) algorithm. Nonetheless, a novel problem arises in EON, known as the fragmentation problem. Indeed, as connections are dynamically established and terminated, spectrum may become fragmented and jeopardize the establishment of future connections. In this situation, the contiguity and continuity constraints in the RSA problem are harder to be guaranteed and therefore connections' blocking probability increases. In this paper we present and analyse some fragmentation-aware RSA algorithms currently found in the literature and analyse their performance when implemented alone or in tandem.

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.

Elastic optical networks are seen as a promising solution to improve spectrum utilization efficiency by utilizing flex-grid optical orthogonal frequency division multiplexing technology and facilitating flexible bandwidth allocation to services with heterogeneous demands. With dramatic growth of Internet traffic and imminent fiber capacity exhaustion, multiple fibers per link are required to accommodate increasing demands. In this paper, we investigate path selection and spectrum management for heterogeneous bandwidth requests by taking the network topology and expected traffic pattern into account. A novel and efficient solution for path selection and spectrum assignment that optimizes the state of the network after assignment is proposed. We first develop integer linear programming formulations to calculate path selection probabilities offline. Then, we propose a spectrum partition scheme that provides a particular spectrum range for each request size. A next-state-aware spectrum assignment algorithm with resource sharing among partitions is then introduced. We use the demand blocking ratio for dynamically arriving requests as the performance indicator. Simulation results indicate the effectiveness of our proposed schemes for routing and spectrum assignment, as they perform 1 to 2 orders of magnitude better than several baseline schemes.

In Elastic Optical Networks (EON), the literature usually measures QoT (Quality of Transmission) by the Optical Signal-to-Noise Ratio (OSNR) or estimated maximum transparent reach of the modulation technique adopted by the circuit. This paper evaluates the Quality of Transmission (QoT) margins adopted in traditional Routing, Modulation Level, and Spectrum Assignment (RMLSA) algorithms that quantity QoT through the maximum transparent reach of the modulation techniques. A RMLSA algorithm is proposed that categorizes the minimum margins that must be adopted for the establishment of new circuits, based on their expected degeneration and the impact it will have on the already established optical circuits. Simulation results show that the proposed minimum margins associated with circuit invigoration present better results than algorithms that propose a fairer margin or evaluate QoT through the maximum transparent reach. The proposal showed a reduction of up to 89% of bandwidth blocking rate and with a runtime performance similar to the simpler algorithms that evaluate QoT by distance.

A fragmentation-avoiding spectrum assignment strategy based on spectrum partition is proposed, which is used to resolve the spectrum fragmentation problem in elastic optical networks. For alleviating spectrum fragmentation, a spectrum partition policy, splitting the whole optical spectrum into several dedicated partitions, is presented. Based on this, a joint first-last-fit spectrum assignment policy is presented to enhance the probability of successful transmission of request and spectrum efficiency, where each partition is first used to transmit requests with the same rate in the first-fit policy; and other partitions are used to search available spectrum resources in the last-fit policy when there are no available spectrum resources in the dedicated partition. Meanwhile, a partition selection formula is designed to minimize the interference of spectrum resources during the last-fit spectrum assignment. Moreover, a reconfiguration mechanism, moving requests that are not transmitted in their dedicated partition to their dedicated partition, is also studied. The simulation results indicate that the proposed algorithm can reduce the bandwidth blocking probability and improve spectrum efficiency.

As the services in elastic optical networks (EONs) are bandwidth-intensive, unpredictable and dynamic, increasing network factors are emerging to affect the performance of network survivable planning and operation from network capacity to efficiency. Most of the traditional protection and restoration approaches may become before long inefficient due to the improvement of a particular network performance metric always at the expense of others. We argue that it would be more beneficial for comprehensive optimization of network performance to consider main network metrics jointly. Moreover, the highly dynamic features of EONs call for the new generation of machine learning-based solutions that are flexible and adaptable to cope with the dynamic nature of services to perform analytics. In this paper, we investigate the problem of global optimization of network performance under survivable EON environment. Specifically, a criterion, named the whole network cost-effectiveness value with survivability (WCES), is defined to measure the overall network performance by balancing the interaction among main network metrics. Then we propose a deep reinforcement learning (DRL) -based heuristic with the objective of improving overall network performance, in which two agents are utilized to provide working and protection schemes converging toward better survivable routing, modulation level and spectrum assignment (S-RMLSA) policies. Numerical results show that the proposed criterion can efficiently measure the overall network performance, and the double-agent DRL-based heuristic can greatly improve WCES while ensuring the network survivability and paying the acceptable extra consumption of request blocking probability.

This paper addresses one of the main tasks in transparent static elastic optical networks (EONs), known as the routing, modulation level, and spectrum assignment (RMLSA) problem. We present, for the first time, a two-stage RMLSA solution, focusing on reducing spectrum consumption (or network capacity). The first macro stage, called least demand bandwidth balance (LDBB), relies on a physical layer impairment (PLI) model to jointly compute the connections’ route and modulation level (RML). We use a new balancing criterion that effectively distributes each network link’s frequency slot unit (FSU) demands, exemplifying three different balancing functions based on the maximum number of FSUs on the links and the total number of FSUs demanded and the cost of the route. In the last macro stage, using all connections chosen paths, we perform the spectrum assignment (SA) process using two specific connections prioritization criteria. We propose two SA algorithms, called sliding-fit (SF) and parcel-fit (PF), reducing the spectrum consumption. These algorithms change the SA paradigm by searching connections for a given subset of the frequency spectrum, contrary to the search of FSUs for a given connection in standard approaches. In all cases, our solution exhibited a lower total network capacity than the commonly used strategies found in the literature, with an average network capacity reduction of 5.7 % FSUs. In addition, our proposal may be used to easily dimension network capacity and determine how many extra resources may be needed to attend to all network users.

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

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.

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.

In this paper, we propose a defragmentation based load balancing technique for efficiently undertaking routing and spectrum assignment (RSA), and minimizing the fragmentation problem in elastic optical network (EON). In EON, after connections terminate, they leave behind spectrum gaps which con not be re-assigned. To counter this condition, in Defragmentation based Load Balancing Routing and Spectrum Assignment (DLBRSA), the existing connections are reconfigured. At the time of defragmentation, for route selection, among the available shortest routes, the route with the largest chunk of contiguous frequency slots (FSs) is chosen. DLBRSA has three advantages over the conventional Shortest Path RSA (SPRSA) technique: (1) defragmentation increases the network resource utilization, (2) load balancing on the basis of the largest available FS chunk along the route ensures uniform spectrum allocation, and (3) defragmentation ensures that the route length of the request is minimum. The performance of the DLBRSA is analyzed in reference to a benchmark, SPRSA strategy. The comparison is done on the metrics of bandwidth rejected, and the percentage of total network capacity allocated for the EON and NSFNET network topologies. These two parameters are evaluated under the two scenarios of increase in: network load (in Erlang) and number of FSs demand. Simulation results show lower bandwidth blocking probability of DLBRSA from 6.53% to 8.96% under the different load conditions. In addition, decrease of network resource utilization is observed, when we compare the proposed DLBRSA with SPRSA the existing strategy.