Distance Adaptive Dynamic Routing and Spectrum Allocation in Elastic Optical Networks with Shared Backup Path Protection

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.

Spectrum Expansion/Contraction and Survivable Routing and Spectrum Assignment problems on EONs with time-varying traffic

The emergence of Elastic Optical Networks (EON) has brought new conceptions in the operations of optical networks, improving its flexibility and efficiency. The routing and spectrum assignment (RSA) is one of the key problems in EON which deals with resource allocation. In order to reduce the bandwidth blocking ratio on the network, recently, Auxiliary-Graph-Model approaches propose spectrum reservation schemes to reduce the network exhaustion probability. However, these approaches do not take into account the energy expenditure caused by these schemes. In this work, we use an auxiliary graph model to design a new RSA heuristic algorithm to improve the network energy consumption without losses in bandwidth blocking rate. Numerical results show that our proposal may provide a reduction of up to 54% in the bandwidth blocking ratio and achieve a gain of up to 51% in energy efficiency compared to literature.

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.

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.

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.

Recent work has proposed the concept of failure-independent path-protecting (FIPP) p-cycles as a pre-connected, failure independent, path-protecting network architecture [A. Kodian, W. D. Grover (2005)]. FIPP p-cycles extend p-cycles by adding the property, like shared backup path protection (SBPP), of providing end-to-end failure independent path switching against either span or node failures. Especially in a transparent or translucent optical network, the property of pre-cross-connection of protection paths can be even more important than just increasing restoration-speed: when optical protection paths are pre-cross-connected, they can be guaranteed in advance to work when required. FIPP p-cycles therefore offer a fully pre-connected, alternative to SBPP in which protection paths must be assembled on the fly from spare wavelength channels. Design results from small networks in [A. Kodian, W. D. Grover (2005)] showed that FIPP p-cycle designs can be as efficient as SBPP but it is very difficult to design larger networks using the ILP design model in [A. Kodian, W. D. Grover (2005)]. We now develop a new ILP model and a related heuristic method for FIPP p-cycle design that produces network designs with much faster runtimes. Results indicate that the heuristic generates FIPP p-cycle designs that have total capacity costs within 10-18% of optimally designed SBPP solutions.

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

With flexibility in optical layer, elastic optical network (EON) has been considered as a competitive candidate to architect next-generation backbone networks. Routing and spectrum assignment (RSA) is a key problem for the service provisioning in EONs. The RSA problem is NP-hard even in elastic optical rings. Numerous heuristics have been proposed, and they can generally be categorized into two types: Route-First (RF) and Spectrum-First (SF). Although most previous work demonstrated by numerical simulations that the SF algorithms always outperform the RF ones, there is a lack of theoretical analysis on the reasons causing the performance difference between the two types of RSA algorithms. In this paper, we aim at proposing a unified theoretical framework for the performance analysis of RSA algorithms by leveraging conflict graphs, which offers a new perception on the optimality of RSA algorithms. To validate the proposed framework, we apply it in elastic optical rings (with cycle topology), and theoretically analyze the number of edges of the conflict graphs for RF and SF algorithms. Different from the literature, we obtain an interesting observation that neither the RF nor the SF can surpass the other in elastic optical rings under different traffic distributions, and their performances have a strong correlation to the edge count of their conflict graph. This observation provides a new perspective, i.e., conflict graph, to explore the property of RSA algorithms.

This paper presents the features of an advanced software simulator for the Elastic Optical Network (EON) - Complex Elastic Optical Networks Simulator (CEONS). The CEONS is as a test environment for solving three main issues addressed in EON: Routing and Spectrum Assignment (RSA) problems; Routing, Modulation and Spectrum Assignment (RMSA) problems, and addressing regenerator placement problem. With a universal API, users can design their own algorithms in any programming language and implement them in the simulator as plugins to solve the problems mentioned above. The ease and versatility of implementing the algorithms allows usage of the CEONS in advanced problems and for the introduction of EON technology.

We focus on dynamic crosstalk-aware lightpath provisioning in translucent space-division multiplexing (SDM) elastic optical networks, in which spectral super-channels are carried over multi-core fibers (MCFs), distance-adaptive transmission is considered, and back-to-back (B2B) signal regeneration is applied. We aim at establishing lightpaths for connection requests in such a way that the inter-core crosstalk (XT) impairment affecting the quality of lightpaths in the network does not exceed allowable threshold levels. To this end, we propose and analyze a method that is based on per-core static/worst-case XT estimation. This method is implemented in a dynamic XT-aware routing, spatial mode, and spectrum allocation (RSSA) algorithm, which is used to solve the lightpath provisioning problem in an efficient way, such that the bandwidth blocking probability is minimized. The performed extensive simulation experiments in realistic network scenarios show a significant impact of this method on network performance and motivate for its application instead of commonly used per-fiber worst-case XT estimation.

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.

De-multiplexing the required spectrum in a traffic demand into multiple non-adjacent granular spectrums for dynamic traffic grooming in EON

In the past few decades, the architecture of optical networks has undergone significant evolution, from the earliest wavelength-division multiplexing (WDM) optical networks to elastic optical networks (EONs) and later to space-division multiplexing (SDM) EONs, to address the continuous growth of Internet traffic. By 2024, Pbps-level optical networks are expected, far exceeding the capacity limit of single-mode fibers. The massive SDM era is on the horizon. In this context, a newly designed architecture for optical networks called the spatial channel network (SCN) architecture, which achieves high cost efficiency by means of practical hierarchical optical cross-connects, has recently been proposed. However, the evolution of optical network architectures will simultaneously present challenges related to network optimization. For instance, with the evolution from WDM optical networks to EONs, the kernel network optimization problem was transformed from the routing and wavelength assignment (RWA) problem into the routing and spectrum assignment (RSA) problem due to the additionally introduced constraint of spectrum contiguity. Similarly, specially designed algorithms are also expected to be essential for addressing the network optimization problem in SCNs. In this paper, we define this new problem as the routing, spatial channel, and spectrum assignment (RSCSA) problem. We propose an integer linear programming (ILP) model and a heuristic algorithm to solve the RSCSA problem. We examine the performance of the proposed approaches via simulation experiments. The results show that both proposed approaches are effective in finding the optimal solutions or solutions close to the lower bounds. To the best of our knowledge, this is the first work to focus on the network optimization problem in SCNs.

We study traffic grooming with shared backup path protection (SBPP) in IP over elastic optical network (EON). Efficient heuristic algorithms are developed to enable joint spare capacity sharing in both IP and optical layer. Results show that two-layer joint spare capacity sharing can significantly improve network capacity utilization and IP-layer protection is more preferable from the perspective of spare capacity sharing efficiency.