Dynamic Cooperative Spectrum Sharing and Defragmentation for Elastic Optical Networks

Spectrum engineering in flexible grid data center optical networks

Service differentiation-based spectrum defragmentation in mixed grid optical networks

The metro section of telecom networks is currently pressured by a strong increase of traffic required by end users. Especially mobile end users are adopting new media-rich services that require high bandwidth. These users are characterized by a geographical mobility this mobility induces significant changes in the traffic pattern at metro level. So future metro networks are expected not only to provide very large capacities but also to support sudden (dynamic) changes of the traffic pattern. An optical metro network based on the concept of flexible spectrum grid can address such requirements in terms of bandwidth and flexibility. In this paper we show the benefits of employing a flexible grid in metro ring networks compared to a fixed-grid WDM case, under dynamic (changing) traffic. The adoption of flexible grid enables an effective spectrum utilization resulting in network blocking a few orders of magnitude lower with respect to fixed grid case.

Compared to traditional wavelength division multiplexing (WDM) networks, orthogonal frequency division multiplexing (OFDM)-based flexible optical networks provide better spectral efficiency due to their flexible bandwidth allocation capability and fine granularity. Survivability is a crucial issue in OFDM-based flexible optical networks. Recently we proposed a new survivable multi-path provisioning scheme (MPP) that efficiently supports demands with flexible protection requirement in OFDM-based optical networks and studied the static survivable multipath routing and spectrum allocation (SM-RSA) problem, which aims to accommodate a given set of demands with minimum utilized spectrum. We have showed that the MPP scheme achieves higher spectral efficiency than the traditional single-path provisioning (SPP) scheme. In this paper, we study the dynamic SM-RSA problem, which selects multiple routes and allocates spectrum on these routes for a given demand as it arrives at the network. We develop an integer linear programming (ILP) model as well as a heuristic algorithm for the dynamic SM-RSA problem. We conduct simulations to study the advantage of MPP over SPP for the dynamic traffic scenario in terms of blocking performance and fairness. We also compare the performance of the MPP heuristic algorithm and the ILP model.

The rapid escalation of Internet traffic and increasingly heterogeneous service demands impose stringent requirements on optical networks for dynamic resource scheduling, efficient spectrum utilization, and automated operation. Elastic optical networks (EONs) are regarded as a promising solution, yet their performance remains constrained by two critical challenges: routing, modulation format, and spectrum allocation (RMSA) and spectrum defragmentation (SD). Existing approaches predominantly focus on optimizing one of these tasks, which may lead to limited adaptability and suboptimal network efficiency. To address this gap, we propose an asynchronous cooperative multi-agent deep reinforcement learning framework, termed MADRL-JRASD, for the joint optimization of RMSA and proactive SD. The framework incorporates an RMSA agent with dynamic allocation capability and an SD agent with autonomous decision-making ability, coordinated through an asynchronous architecture that enables adaptive responses to environmental changes. Invalid-action masking and carefully designed reward functions are further integrated to enhance training stability and convergence. Comprehensive evaluations over three representative topologies demonstrate that MADRL-JRASD reduces the blocking probability by up to 81% compared with RMSA heuristics without SD and achieves an 85% reduction in overhead relative to heuristic algorithms combining RMSA and SD that attain similar blocking performance. Moreover, the sensitivity analysis shows that the SD agent improves spectrum utilization and that multi-agent cooperation enhances global decision coordination, while action masking and reward design jointly strengthen the convergence and efficiency of MADRL-JRASD.

In order to fully utilize scarce spectrum resources, dynamic spectrum allocation becomes a promising approach to increase the spectrum efficiency for wireless networks. However, the collusion among selfish network users may seriously deteriorate the efficiency of dynamic spectrum sharing. The network users' behaviors and dynamics need to be taken into consideration for efficient and robust spectrum allocation. In this paper, we model the spectrum allocation in wireless networks with multiple selfish legacy spectrum holders and unlicensed users as multi-stage dynamic games. In order to combat user collusion, we propose a pricing-based collusion-resistant dynamic spectrum allocation approach to optimize overall spectrum efficiency, while not only keeping the participating incentives of the selfish users but also combating possible user collusion. The simulation results show that the proposed scheme achieves high efficiency of spectrum usage even with the presence of severe user collusion.

In this paper, we propose a grouping-based dynamic routing, core, and spectrum allocation (RCSA) method for preventing spectrum fragmentation and inter-core crosstalk in elastic optical path networks based on multi-core fiber environments. Multi-core fibers enable us to considerably enhance the transmission capacity of optical links; however, this induces inter-core crosstalk, which degrades the quality of optical signals. We should thus avoid using the same frequency bands in adjacent cores in order to ensure high-quality communications. However, this simple strategy leads to inefficient use of frequency-spectrum resources, resulting in spectrum fragmentation and a high blocking probability for lightpath establishment. The proposed method allows one to overcome this difficulty by grouping lightpath-setup requests according to their required number of frequency slots. By assigning lightpath-setup requests belonging to the same group to cores according to their priority, the proposed method aims to suppress inter-core crosstalk. Furthermore, the proposed method is designed to mitigate spectrum fragmentation by determining the prioritized frequency bandwidth for lightpath-setup requests according to their required number of frequency slots. We show that the proposed method reduces the blocking of lightpath establishment while suppressing inter-core crosstalk through simulation experiments.

In this paper, we propose a dynamic spectrum allocation (DSA) scheme DeepBlocks at the backdrop of sixth-generation (6G) communication networks that address the challenges of fixed spectrum allocations (FSA). The scheme exploits the advantages of deep-Q-network (DQN) and minimizes the search state explosion through a reward-penalty framework. A dynamic allocation of unallocated resource blocks (RBs) to mobile units (MUs) is carried out and once the allocation of RBs is complete, we integrate blockchain (BC) to record the transactional ledgers. The resource usage of MUs is recorded through smart contracts (SCs). We model the proposed scheme as a convex optimization problem, and subproblems are decomposed into a Pareto-optimal solution via Techebyecheff decomposition. In the simulation, we compare our scheme against FSA, and fifth-generation (5G) based DSA schemes like reinforcement learning (RL), deep neural networks (DNN)-based, and duelling DQN based schemes. The comparative analysis of 6G-DQN is modeled in terms of reward formulation, scalability of 6G-DQN-assisted DSA, and profit scenarios of BC-based allocation through intelligent channel control. The scheme proposes significant findings, with the best fit learning rate of 0.0001, and takes 500 episodes to converge to 60 total resource blocks. The servicing latency of the scheme is 272.4 ms, compared to 2010 ms in the duelling DQN approach. In spectrum allocation, an improvement of 26.32% is observed against non-DQN approaches, and 13.57% in the fairness parameter for spectrum allocation due to BC inclusion. The findings present the scheme efficacy for DSA over the aforementioned conventional approaches.

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.

<p>In this work, eavesdropping-aware routing and spectrum allocation (RSA) techniques are proposed for elastic optical networks (EONs) using orthogonal frequency division multiplexing (OFDM). To introduce physical (optical) layer security and protect these networks against eavesdropping attacks, spread spectrum (SS) with signal overlapping techniques are used to encode each requested confidential connection. In order to attain access to the signal and compromise a confidential connection, an eavesdropper will now have to lock on the correct frequency, determine the correct code and symbol sequence amongst copropagated overlapped signals, and decode the signal. Different routing strategies and a novel spectrum allocation technique are proposed in an attempt to add an extra layer of security for confidential connections, while also considering spectrum utilization. Performance results demonstrate that while each confidential connection now requires more spectrum as a result of spreading in the bandwidth domain, the overall network spectrum usage is not increased proportionally to the spreading factor due to the utilization of spectrum overlapping techniques.</p>

Allowing Secondary Users (SUs) to access the licensed spectrum without causing harmful interference to the Primary Users (PUs) is crucial in enabling the Cognitive Radio (CR) technology. In order to increase the utilization of the spectrum bands, we propose a Dynamic Spectrum Allocation (DSA) algorithm that integrates both interweave and underlay spectrum access schemes. The proposed algorithm will jointly take into account the geographical locations of the nodes, the correlated shadow fading, the interference between the primary and the secondary networks, the interference between SUs that are transmitting on the same channel, and the communications activity of the users. Moreover, a suboptimal heuristic DSA algorithm that jointly takes into consideration all of the aforementioned issues, while requiring low computational- and time-costs, is developed. Simulation results show that the proposed algorithm provides a good success rate and outperforms classical spectrum allocation algorithms.

Over the past decade, we have seen a substantial amount of research on elastic optical networks (EONs), showing great promise towards dramatically improving transmission capacity compared to traditional optical networks. The main concern is that the achievable transmission capacity for a given fiber will reach the physical limit soon in the case of single-core fibers. Multi-core fiber (MCF) has been proposed as an innovative alternative which is based on the concept of space-division multiplexing (SDM). We endeavour to work on a Crosstalk Elimination and Spectrum Defragmentation based Routing and Spectrum Allocation (CESD-RSA) algorithm has been proposed which is based on a predefined metric, which measures the spectrum status in the SDM-EONs. Past research has indicated the dependence of crosstalk effect in MCF on the assignment of signals in the context of the spectrum and the core. This specifically entails a study of the Routing, Core and Spectrum allocation in a flexi-grid multicore network. In the end we shall endeavour to evaluate the proposed method using computer simulations.KeywordsWDMSDMEONMCFRSASF

QoS-aware distributed spectrum sharing for heterogeneous wireless cognitive networks

In future optical networks, versatile functionalities will be required for the optical network subsystems to fully utilize the spectral resources with low energy consumption. The key technologies are the spectral efficient MUX/DEMUX technique and flexible control of optical channels with high frequency granularity. An orthogonal frequency division multiplexing (OFDM) and Nyquist wavelength division multiplexing (N-WDM) are the most promising candidates of spectral efficient multiplexing techniques, and all-optical (AO) processing is expected to reduce the energy consumption. In an AO-OFDM systems, discrete Fourier transform (DFT) and inverse DFT (IDFT) are performed in optical domain by specially designed arrayed waveguide gratings (AWGs). In our experiment, 12.5 GHz spaced AO-OFDM system has been successfully demonstrated with no guard interval. In N-WDM systems, the Nyquist signal is generated by using carrier-suppressed return-to-zero (CS-RZ) signal and optical Nyquist filtering, which is achieved with two flat-top AWGs and optical interleaver, and the 25 Gbaud signals are successfully multiplexed in the experiment. Although both AO-OFDM and N-WDM can achieve the highest spectral efficiency, N-WDM is more suitable for flexible optical networks. This is because the N-WDM channels have less spectral overlap with the other channels than AO-OFDM, owing to its rectangular shaped compact spectrum. Therefore, N-WDM channel can be easily multiplexed and demultiplexed by optical filters. At an optical network node, channel defragmentation is indispensable technology to flexibly control the optical channels. We have experimentally demonstrated a format independent optical channel defragmentation with N-WDM signal. We believe these technologies are promising for future flexible optical networks.

In order to improve spectrum utilization, dynamic spectrum allocation DSA schemes with interference management have been widely investigated, and a special interest is in the current heterogeneous wireless network HWN environment. In the previous work, the approach that guarantees quality of service for the cell-boundary user is extensively used in the DSA scheme. However, such approach gives a pessimistic result. In this paper, we design a DSA scheme for the HWN system, which adopts relatively accurate interference constraints. First, considering that users may randomly locate over the cell, we propose interference constraints across the cell coverage, in which the interference experienced at a point is controlled below the level suffered when using fixed spectrum allocation in only a single network, and the proportion of the cell area where interference is controlled reaches the required area coverage probability. Then under the interference constraints, we formulate the downlink DSA scheme as a combinatorial optimization problem. As the problem is NP-hard, to reduce the computational complexity, we propose two greedy heuristic algorithms for its solution. Simulation results show that the DSA scheme could improve the total spectrum utility for operators and increase the satisfaction rate of spectrum demands for base stations. Copyright © 2013 John Wiley & Sons, Ltd.