Node Importance Based Protection in Power-Grid Optical Backbone Communication Networks

Power-grid optical backbone communication network is a special communication network serving for power system. With the development of new internet technology, there are more and more services carried by power-grid optical backbone communication networks. It plays an important role in the protection of nodes, especially important nodes which often carry important information of the network, when the network is under heavy traffic load. Hench, to solve this problem, we propose the concept of node importance and design a node importance-based protection algorithm under heavy traffic load scenario in power-grid optical backbone communication networks. Simulation results show that the proposed node importance based protection algorithm can obviously reduce blocking probability of the important nodes and improve the performance of the entire network in terms of blocking probability.

Spectrum Availability Aware Routing and Resource Allocation for Point-to-Multipoint Services in Mixed-Grid Optical Networks

Mixed-grid optical networks are in a migration state where fixed-grid and flex-grid optical networks coexist. To carry point-to-multipoint (P2MP) services in mixed-grid optical networks, routing and resource allocation (RRA) problems need to be solved. Once the RRA fails, services will be blocked and then influence quality of service. The minimized spectrum for satisfying the bandwidth request of services is called as a frequency block (FB). For a service, the total number of available FBs embodies the spectrum availability on a link. Because the fixed-grid and flex-grid links have different channel spacing, spectrum availability on fixed-grid and flex-grid links needs different evaluation method. We propose a RRA algorithm in mixed-grid optical networks for P2MP services by being aware of spectrum availability. The spectrum availability is evaluated according to fixed-grid and flex-grid constraints. Our proposed algorithm achieves the lower blocking probability (BP) than that of benchmark RRA algorithms according to simulation results.

A Research on Routing and Spectrum Allocation Algorithm for Elastic Optical Networks Based on Deep Learning

Dynamic allocation request and spectrum release will lead to spectrum fragmentation, which will affect the allocation of subsequent services and spectrum resource utilization of elastic optical network. This paper proposes a new routing and spectrum allocation algorithm based on deep learning, which will find the best routing and spectrum allocation method for a specific network, so as to improve the overall network performance. Simulation results show that compared with the traditional resource allocation strategy, the neural network model used in this paper can improve the degree of spectrum fragmentation and reduce the network blocking probability.

Quality Enhancement In A mm-Wave Multi-hop, Multi-Tier Heterogeneous 5G Network Architecture

Millimetre-wave ultra-dense high capacity networks by providing an important component of future 5G cellular systems, by providing extremely high capacity to end users. Disparate types of users coexist in such scenarios, which can make the heterogeneous network unfair in terms of allocation of resources. A mechanism is required for effective spectrum sharing and to achieve overall system fairness. In this paper, an analytical model is suggested, which is based on a two-dimensional Markov state-transition diagram, to help set the parameter values to control the issuance of resources in coexistence layouts. A restriction approach is further implemented to gain a fair balance of the Grade-of-Service for both user groups using the User Admission Control mechanism. The developed mechanism restricts access to various channel resources for users with complete choice to give a greater probability of access to different users with limited resource options. Various levels of restriction are investigated in order to offer a balanced low-blocking probability performance to both user groups in order to improve the overall network fairness. Also, the proposed approach could provide a precise level of Grade-of-Service guarantee for both the user groups if sufficient flexibility is available within the whole network. Our simulation results show that approximately 30% to 45% enhancement, in terms of grade of service (GoS), could be achieved in high to medium loads by restricting some users' flexibility.

LBFA: A Load-Balanced and Fragmentation-Aware Resource Allocation Algorithm in Space-Division Multiplexing Elastic Optical Networks

We consider a space-division multiplexing elastic optical network (SDM-EON) that supports super-channels (SChs). A Sch comprises a set of contiguous frequency slots on multiple cores in a multi-core fiber. The problem of finding a lightpath using SChs involves routing, modulation, spectrum and core assignment (RMSCA). To minimize the request blocking probability (RBP), two critical issues must be addressed. First, routing and modulation assignment (RMA) should not cause hotspots, or overutilized links. Second, spectrum and core assignment (SCA) should aim at minimizing fragmentation, or small frequency slot blocks that can hardly be utilized by future requests. In this paper, a pre-computation method is first proposed for better load balancing in RMA. Then an efficient fragmentation-aware SCA is proposed based on a new fragmentation metric that measures both the spectral and spatial fragmentation. With the enhanced RMA and SCA, a joint load-balanced and fragmentation-aware algorithm called LBFA is designed to solve the RMSCA problem. As compared with the existing algorithms, simulation results show that our LBFA provides significant reduction in RBP.

TDTS: Three-Dimensional Traffic Scheduling in Optical Fronthaul Networks with Conv-LSTM

Given the more intensive deployments of emerging Internet of Things applications with beyond-fifth-generation communication, the access network becomes bandwidth-hungry to support more kinds of services, requiring higher resource utilization of the optical fronthaul network. To enhance resource utilization, this study novelly proposed a three-dimensional traffic scheduling (TDTS) scheme in the optical fronthaul network. Specifically, large and mixed traffic data with multiple different requirements were firstly divided according to three-dimensions parameters of traffic requests, i.e., arriving time, transmission tolerance delay, and bandwidth requirements, forming eight types of traffic model. Then, historical traffic data with division results were put into convolutional-long short-term memory (Conv-LSTM) strategy for traffic prediction, obtaining a clear traffic pattern. Next, the traffic processing order was supported by a priority evaluation factor that was measured by traffic status of the link and network characteristics comprehensively. Finally, following the priority, the proposed TDTS scheme assigned the resource to traffic requests according to their results of traffic division, prediction, and processing order with the shortest path routing and first-fit spectrum allocation policies. Simulation results demonstrated that the proposed TDTS scheme, on the premise of accurate traffic prediction, could outperform conventional resource-allocation schemes in terms of blocking probability and resource utilization.

Dynamic Routing and Spectrum Assignment based on the Availability of Consecutive Sub-channels in Flexible-grid Optical Networks

Variable bandwidth channels can be created in Flexible Grid Optical Networks using Optical Orthogonal Frequency Division Multiplexing (O-OFDM). This allows more efficient use of spectrum by allocating integral multiple of basic bandwidth slot to the lightpath requests. In these networks, the constraint of keeping all the allocated slots together is added when deciding the routes for the requests. This constraint is called the contiguity constraint, which makes the routing and spectrum arrangement algorithms more challenging. In any network, the lightpath requests will arrive and depart dynamically and invariably lead to spectrum fragmentation. Hence network will have to reduce the maximum possible utilization as well as increased blocking probability. In this paper, we have presented an improvised Routing and Spectrum Assignment (RSA) algorithm using consecutive spectrum slots 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 the other algorithms reported in the recent past.

Dynamic Routing and Spectrum Assignment based on the Availability of Consecutive Sub-channels in Flexible-grid Optical Networks

Variable bandwidth channels can be created in Flexible Grid Optical Networks using Optical Orthogonal Frequency Division Multiplexing (O-OFDM). This allows more efficient use of spectrum by allocating integral multiple of basic bandwidth slot to the lightpath requests. In these networks, the constraint of keeping all the allocated slots together is added when deciding the routes for the requests. This constraint is called the contiguity constraint, which makes the routing and spectrum arrangement algorithms more challenging. In any network, the lightpath requests will arrive and depart dynamically and invariably lead to spectrum fragmentation. Hence network will have to reduce the maximum possible utilization as well as increased blocking probability. In this paper, we have presented an improvised Routing and Spectrum Assignment (RSA) algorithm using consecutive spectrum slots 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 the other algorithms reported in the recent past.

Towards an Efficient and Exact Algorithm for Dynamic Dedicated Path Protection

We present a novel algorithm for dynamic routing with dedicated path protection which, as the presented simulation results suggest, can be efficient and exact. We present the algorithm in the setting of optical networks, but it should be applicable to other networks, where services have to be protected, and where the network resources are finite and discrete, e.g., wireless radio or networks capable of advance resource reservation. To the best of our knowledge, we are the first to propose an algorithm for this long-standing fundamental problem, which can be efficient and exact, as suggested by simulation results. The algorithm can be efficient because it can solve large problems, and it can be exact because its results are optimal, as demonstrated and corroborated by simulations. We offer a worst-case analysis to argue that the search space is polynomially upper bounded. Network operations, management, and control require efficient and exact algorithms, especially now, when greater emphasis is placed on network performance, reliability, softwarization, agility, and return on investment. The proposed algorithm uses our generic Dijkstra algorithm on a search graph generated “on-the-fly” based on the input graph. We corroborated the optimality of the results of the proposed algorithm with brute-force enumeration for networks up to 15 nodes large. We present the extensive simulation results of dedicated-path protection with signal modulation constraints for elastic optical networks of 25, 50, and 100 nodes, and with 160, 320, and 640 spectrum units. We also compare the bandwidth blocking probability with the commonly-used edge-exclusion algorithm. We had 48,600 simulation runs with about 41 million searches.