Efficient Dynamic Routing and Spectrum Assignment for Multifiber Elastic Optical Networks

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

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

We consider dynamic Routing and Spectrum Assignment problem in elastic optical networks with multiple fibers per link. The proposed path selection and spectrum management scheme is demonstrated to improve spectrum efficiency.

Elastic optical network is the promising solution to improve spectrum efficiency by utilizing flex-grid optical orthogonal frequency division multiplexing technology and facilitating the flexible bandwidth allocation to services with heterogeneous demands. Future generation needs a reliable and fast transfer of information which leads to increase in demand bandwidth and therefore the necessity of optimized and improved spectrum management occurs. High resolution remote sensing have been adapted to sample growing crop in the hilly or high altitude field (like tea or apple bagan) to keep track of the crops growing in the field and also for the wild life monitoring in sanctuary or in national park to observe their health and behavior. One of the main challenges over here is the development of robust calibration and validation methodologies for transmission of these critical information through optical network for fast and reliable communication. In this article, authors have proposed Grey Wolf Optimization (GWO) based algorithm to provide the solution for the above mentioned challenge. The simulation results show that proposed approach provides significant improvement for spectrum efficiency with respect to reference methods.

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.

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

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.

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.

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.

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.

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.

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.

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.

In the current work, we formulate a dynamic spectrum assignment (DSA) technique to allocate the experimental licensed 95 GHz Tera-Hertz spectrum to the mobile service providers (MSPs) in India in view of achieving high spectrum usage. For a fixed term of renewal (ToR), the formulated DSA technique compares the number of consumers of an MSP with all the remaining MSPs and then assigns the spectrum accordingly. The DSA then updates the assigned spectrum to an MSP at every ToR in accordance with variation in the amount of consumers compared to the previous ToR. The DSA technique is formulated such that it finds the optimal spectrum amount required by every MSP during each ToR. Also, the mean capacity (MC), spectral efficiency (SE), energy efficiency (EE), and cost efficiency (CE) are derived for each MSP. The aforementioned metrics are used to compare the performance of DSA with the static spectrum assignment (SSA) method, which assigns the spectrum to any MSP without accounting for the actual requirement by the consumer. We conduct extensive simulations considering a specific scenario with four MSPs, and the results demonstrate that the DSA technique is able to meet the demands of the 6G wireless systems as it is able to reuse the available spectrum for every MSP for a fewer number of cells of approximately 38% reduced amount of buildings. Further, the results also demonstrate that, in comparison to the traditional static spectrum assignment (SSA) method, DSA improves the MC and SE by 20% and the EE and CE by 25%.

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