Dynamic Routing and Spectrum Assignment for Multi-fiber Elastic Optical Networks

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.

We investigate the problem of dynamic routing and spectrum assignment for advance reservation anycast requests using a novel algorithm called Delayed Spectrum Allocation (DSA) which delays allocation of resources until immediately before transmission begins. We evaluate the flexible window STSD (demands that specify start-time and duration) to further improve request blocking. Through extensive simulation results, we show that anycast with flexible STSD using DSA approach can significantly reduce blocking probability of anycast and unicast requests compared to traditional Immediate Spectrum Allocation (ISA). The improvement is up to 50 percent in unicast traffic and even higher in anycasting. We also propose balanced routing for anycast algorithms to reduce the blocking.

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.

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.

In this paper, we compare performance of fixed-grid Wavelength Division Multiplexing (WDM) and Elastic Optical Networks (EONs) in dynamic provisioning of many-to-many (m2m) flows. Currently, with a growth of services relying on many-to-many communication paradigm such as distributed computing, inter-Data Center communication, content delivery networking or other requiring high-bandwidth in group communication, it is vital to deliver new solutions facilitating these demanding transmissions. Therefore, the authors investigate provisioning of m2m traffic in high-performance optical networks. This work focuses on dynamic Routing and Wavelength Assignment (RWA) problem in WDM networks as well as Routing and Spectrum Allocation (RSA) problem in EONs for m2m flows using replicated communication through auxiliary rendezvous servers.

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.

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%.

Novel applications running on top of wireless sensor networks set new QoS requirements, demand devices' seamless connectivity, and call for new communication paradigms such as opportunistic spectrum access. However, realization of opportunistic spectrum access without causing interference to primary users poses significant challenges that are further exacerbated by the power constrained nature of wireless sensors and the QoS requirements of the supported applications. In this work we consider the problem of dynamic spectrum assignment in opportunistic access spectrum bands in the context of cognitive wireless sensor networks. We propose a dynamic spectrum assignment scheme that establishes a virtual link, between wireless sensors, which exhibits minimal power consumption and deterministic capacity. The virtual link is created on top of opportunistic and free access bands and to this end we utilize cognitive radio technology. The proposed DSA scheme is based on a two-stage stochastic integer program with non-fixed recourse. Numerical results verify the effectiveness of the proposed dynamic spectrum assignment scheme.

Using Optical Orthogonal Frequency Multiplexing (O-OFDM), variable bandwidth channels can be created in Elastic Optical Networks (EON). This allows the use of spectrum more efficiently by allocating integral multiple of basic bandwidth slots to the lightpath requests. Consequently, such networks are also called flexible grid optical networks. It also adds a constraint of keeping all the allocated slots together when deciding the routes for the requests. This constraint called the contiguity constraint makes the routing and spectrum algorithms more challenging. In any network, the lightpath requests will arrive and depart dynamically and will invariably lead to spectrum fragmentation, and hence network will have a reduction in maximum possible utilization due to increased blocking probability. In this paper, we have presented an improvised RSA algorithm that leads to lesser fragmentation. It is evident from the results that the presented RSA algorithm uses adaptive parameters to reduce the blocking probability and fragmentation compared to other algorithms reported in the recent past.

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

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.

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.

Ant colony optimization (ACO) is a probabilistic technique used for solving complex computational problems, such
\nas finding optimal routes in networks. It has been proved to perform better than simulated annealing and genetic algorithm
\napproaches for solving dynamic problems. ACO algorithms can quickly adapt to real-time changes in the system. In this paper, we propose an ACO-based algorithm to solve the dynamic anycast routing and wavelength assignment (RWA) problem in wavelength-routed optical networks. Using extensive simulations, we show that ACO-based anycast RWA significantly reduces blocking probability compared to the fixed shortest-path first (SPF) and other load-balancing and dynamic algorithms.

With the ever increasing demand for optical networks, many decisions about network planning are becoming increasingly challenging. One of these crucial decisions is the network provisioning, known as the Routing and Spectrum Assignment (RSA) problem. What makes this problem practically challenging to service providers is the significant difference in size between the realistic problem instances and the instances that can be solved using the existing algorithms. Motivated to solve larger problem sizes, we propose a decomposition model and a nested column generation algorithm for the RSA problem. Compared to recent studies, the proposed algorithm produces higher-quality solutions for larger data instances quite efficiently. Furthermore, it provides a measure of the solution accuracy, i.e., an upper bound on the maximum distance of the solution obtained compared to the optimal solution.

A novel channel-based model for the problem of routing, space, and spectrum assignment