Optical Network Resources Research Articles

Joint allocation of computing and connectivity resources in survivable inter-datacenter elastic optical networks

Joint allocation of computing and connectivity resources in survivable inter-datacenter elastic optical networks

SDN-enabled path computation element for autonomous multi-band optical transport networks

This paper reports on the design, implementation, and validation of an SDN control plane for multi-band optical networks with externalized path computation. The SDN control plane relies on extending current open and standard interfaces to support dynamic service management and decoupled path computation services on multi-band optical networks while accounting for physical layer impairments, which is critical for successful service provisioning. We detail the multi-band optical network resource management and optimization engine for transparent and translucent networks. The system is experimentally validated in a 22-ROADM BT network with emulated hardware showing the performance of the control plane and the considered workflows.

Reliable adaptive edge-cloud collaborative DNN inference acceleration scheme combining computing and communication resources in optical networks

With the continuous development of the Artificial Intelligence of Things, deep neural network (DNN) models require a larger amount of computing capacity. The emerging edge-cloud collaboration architecture in optical networks is proposed as an effective solution, which combines edge computing with cloud computing to provide faster response and reduce the cloud load for compute-intensive tasks. The multi-layered DNN model can be divided into subtasks that are offloaded to edge and cloud servers for computation in this architecture. In addition, as bearer networks for computing capacity, once a server or link in optical networks fails, a large amount of data can be lost, so the robust reliability of the edge-cloud collaborative optical networks is very important. To solve the above problems, we design a reliable adaptive edge-cloud collaborative DNN inference acceleration scheme (RACAI) combining computing and communication resources. We formulate the RACAI into a mixed integer linear programming model and develop a multi-agent deep reinforcement learning algorithm (MADRL-RACIA) to jointly optimize DNN task partitioning, offloading, and protection. The simulation results show that compared with the benchmark schemes, the proposed MADRL-RACIA can provide a guarantee of reliability for more tasks under latency constraints and reduce the blocking probability.

Evaluation of resource efficiencies for the non-symmetric dynamic wavelength allocation method applied in the P2MP WDM-PON network design

At present days, metropolitan and access communication networks are markedly developing utilizing a variety of technologies. Their bearer communication infrastructures will be mostly exploiting the optical transmission medium where wavelength division multiplexing techniques will play a key role. Wavelength-Division Multiplexed Passive Optical Networks (WDM-PON) attract considerable attention for the next generation optical metropolitan and access networked systems. Simultaneously, the utilization of common optical network resources in wavelength domains will be more important. The main purpose of this paper is presented by the evaluation of resource efficiencies for the non-symmetric dynamic wavelength allocation method applied in the WDM-PON network design with aconventional topology. This contribution introduces a novel non-symmetric Dynamic Wavelength Allocation (DWA) method for a selected network design with the utilization only passive optical splitters in remote nodes. This novel wavelength allocation method is oriented on minimizing anumber of working wavelengths that will be used for compliance of customers’ requests for data transmitting in the common point-to-multipoint WDM–PON network design. For evaluation of wavelength scheduling, a simulation model related to the conventional WDM-PON network design is realized in the MATLAB programming environment is presented with results. Finally, different traffic loading scenarios are determined and, subsequently, resource efficiencies of the presented non-symmetric DWA method are evaluated from aviewpoint of application in future WDM-PON network designs.

Research and analysis of the efficiency fiber-optic communication lines using DWDM technologies

The performance indicators fiber-optic communication lines using spectral technology with separation communication channels are analyzed. The effectiveness of the use network resources optical telecommunication systems using spectral technologies based on the architectural concept of the next NGN (NGN, Next Generation Network) and future FN (FN, Future Network) networks has been studied. This work is devoted to the construction methods for calculating the indicators optical networks and the study methods and tools for improving the efficiency using network and channel resources fiber-optic communication lines using dense spectral multiplexing optical signals with separation communication channels. The problem ensuring effective management channel and network resources in optical communication networks are considered. As a result of the study technology spectral multiplexing, a new approach to the construction of a calculation method is proposed that describes the efficiency managing network and channel resources in fiber-optic communication lines, taking into account the numerous requirements their parameters and transfer characteristics. On the basis of the calculation method, analytical expressions are obtained that allow estimating the resources of the system, indicators informational and spectral efficiency of the functioning fiber-optic communication lines. The results of the research can be applied by cellular operators when designing an optical telecommunications network, in particular, to determine the optimal value of the capacity optical systems based on wavelength multiplexing technology and modulation spectral efficiencies.

Joint optimization of optical path provisioning and VNF placement in vCDN

We consider a joint optimization problem of optical network resources and virtual network function (VNF) placement for efficient content distribution. Current content distribution networks (CDNs) are tightly coupled with network function virtualization (NFV) technologies. A virtual CDN (vCDN) has been intensively investigated to efficiently cope with unpredictable traffic demand. In vCDN, CDN functions are virtually provided as VNF, and we can provide sufficient flexibility regarding the usage of compute resources under traffic demand changes. For the cost-effective CDN services, we must reduce the redundant usage of network resources while improving the efficiency of compute resources. However, a conventional optimal VNF placement technique in vCDN was focused on the efficiency of compute resources, and this can lead to an increase in network cost. To address this issue, we formulate the optimization problem as mixed integer linear programming and then propose a heuristic algorithm called a light-weight VNF placement algorithm in vCDN (LP-vCDN) for reducing network cost while effectively utilizing compute resources. We conducted intensive numerical experiments and demonstrated that LP-vCDN always found solutions of sufficient quality with practical computational overhead.

An Iterative Optimization Approach for Routing, Modulation, and Categorical Spatial Bandwidth Block Allocation to Improve Network Performance for Dynamic Traffic in Elastic Optical Networks

In this work, we have proposed an iterative optimization model for allocating spectral resources in optical networks. The proposed model gives spatial routes and spatial bandwidth allocations in optical networks with variable data-rates, modulation schemes, and optical reach adaptation. We have also proposed an algorithm which allocates continuous and contiguous block of frequency slots (FS) between transponders which forms bandwidth partitions. The primary objective of the bandwidth partition is to reduce spatial fragmentation. The integrated approach includes the routing information from using the optimization model and the categorical spectrum allocation from using the proposed algorithm. The integrated approach has been used for dynamic traffic to improve network performance in terms of bandwidth blocking, link utilization, and fragmentation metrics. It has been shown that the FS utilization (FSU) and link utilization (LU) largely increase in the proposed integrated scheme with 80% LU compared to shortest path first (SPF) routing with LU as low as 20%. Similarly, the standard deviation between FSU in the proposed scheme is approximately 5% compared to 25% in other schemes which shows that the FSU sufficiently increases in the integrated approach.

Deep Reinforcement Learning for Provisioning Virtualized Network Function in Inter-Datacenter Elastic Optical Networks

In today’s datacenters (DCs), IT resources virtualization is leveraged to realize Network Function Virtualization (NFV) over general-purpose servers. Meanwhile, most of the service providers (SPs) are planning to use Virtual Network Functions (VNFs) to provide agile and flexible network services. In service provisioning, the VNF selection and mapping greatly affect IT resource utilization in DCs and spectrum resource utilization in optical networks. This paper proposes a Deep Reinforce Learning (DRL)-based algorithm for VNF provisioning. By selecting appropriate VNFs for the service requests, the algorithm intelligently guarantees efficient reusing of deployed VNFs while consuming fewer spectrum resources in inter-DC elastic optical networks (EONs). To facilitate the decision-making of the DRL agent, we first decompose the complex VNF-based service chaining (VNF-SC) into several VNF components (VNFCs), which can be solved one-by-one in turn. Then, a feature matrix-based encoding scheme is designed to represent the set of the VNFCs, the available DCs for the VNFCs, and the VNFC being operated, i.e., the input of neural networks. In addition, considering the complexity and difficulty of the VNF-SC provisioning problem, Double Deep Q Network (DDQN) is introduced in the proposed algorithm. Finally, compared with the benchmark heuristics, the extensive simulation results in different network topologies show that the proposed algorithm can reduce the IT and spectrum resource consumption by at least 9.6% and 1.6%, which proves the effectiveness of the proposed DRL-based VNF provisioning algorithm.

All-to-all Broadcast in Optical WDM Ring with 2-length Extension and 3-length Extension

All-to-all broadcast communication is to transmit a distinctive data from each node to every other node available in the network. This is a fundamental prerequisite in high performance computing and telecommunication networks including enterprises operating datacenters which may spread across thousands of nodes by means of WDM optical networks. Wavelengths are scarce resources in WDM optical networks. Reducing the wavelengths usage is essential to decrease the price and complication of the network. In this article, a ring network is extended by additionally connecting alternate nodes in order to provide alternate paths so as to reduce the effective number of hops between the communicating nodes and also to reduce the wavelength requirements and this network is referred as a ring network with 2-length extension. Similarly, a ring network is extended by directly linking all nodes which are separated by two intermediate nodes with additional fibers and this network is referred as a ring network with 3-length extension. For the ring network with 2-length extension the optimum wavelength number necessary to establish all-to-all broadcast under unidirectional routing is derived by grouping nonoverlapping connections on a common wavelength. The wavelength number necessary atmost to establish all-to-all broadcast in a unidirectional ring with 3-length extension is derived using longest link first routing algorithm.

QoS-Aware routing, space, and spectrum assignment in space division multiplexing networks

Nowadays, Space Division Multiplexing (SDM) is one of the solutions proposed to increase the capacity and optimal allocation of resources in Elastic Optical Networks (EON). The issue of allocating resources in these networks involves the optimal allocation of route, space and spectrum for the establishment of traffic requests. The quality of service (QoS) provided for establishing traffic requests must vary according to their importance and priority, so that high quality requests require guaranteed bandwidth and higher levels of service than low quality requests. Hence, reducing the blocking probability of high-quality data traffic is one of the most important goals in networks. In this paper, three new QoS-aware algorithms are proposed for route, space and spectrum assignment of dynamic traffic in SDM-EONs that reduce the blocking probability of high-quality requests as follows: Reservation without Common Core (RwoC), Reservation with One Common Core (RwC), and Reservation and Recoring with One Common Core (RRwC). The results of utilizing these algorithms and also adding distance adaptive modulation format show that the blocking rate of high-quality requests is decreased and the general spectrum utilization is increased specially in RRwC algorithm. Of course, this decrease causes a slight increase in the blocking rate of low-quality requests. Another advantage of using the RRwC algorithm is that using the slots with the same index in the recoring method reduces costs because in this case there is no need to change the frequency of transceivers. Since, this algorithm is more cost-effective. In the first proposed algorithm, dedicated cores are designed to create high quality traffic. In the second algorithm, in addition to dedicated cores, a common core is also used between high and low-quality traffic. Finally, the recoring method has been used for high quality traffic to further reduce their blocking rates.

Routing in Elastic Optical Networks Based on Deep Reinforcement Learning

Modern optical network schemes consist of eighty channels involving fixed grids and offering speeds of up to 400 Gbps per channel rendering the allocated bandwidths insufficient during certain timeframes and underutilized during others. These speeds will become inefficient when compared to the accelerated growth of traditional traffic, which threatens to be tripled by 2025. In order to exploit the capacity of elastic optical networks, efficient algorithms are essential. This article assesses Deep reinforcement learning RMCSA algorithms, focused on providing high availability to the allocation of routing, spectrum and modulation resources over a given network topology, in order to determine how to allocate physical resources in optical transport networks and increase capacity while accounting for traffic variability and demands. Reinforcement learning is currently used in many scientific fields for the solution of different problems. In optical networks, this work will use this method to determine the best path and resources for each type of traffic-related demand. Simulations are performed by increasing volumes of variable traffic over a fourteen-node topology. The results show a significant 40% improvement in blocking probability for 22 links with 100 frequency slots compared to current transmission systems. They also reflect low latency, higher speeds, and high availability, which can deliver better quality of service for the end user.

An Effective Evaluation of Wavelength Scheduling for Various WDM-PON Network Designs with Traffic Protection Provision

Recently, metropolitan and access communication networks have markedly developed by utilizing a variety of technologies. Their bearer communication infrastructures will be mostly exploiting the optical transmission medium where wavelength division multiplexing techniques will play an important role. This contribution discusses the symmetric sharing of common optical network resources in wavelength and time domains. Wavelength-Division Multiplexed Passive Optical Networks (WDM-PON) attract considerable attention regarding the next generation of optical metropolitan and access networks. The main purpose of this contribution is presented by the analysis of possible scheduling of wavelengths for our novel hybrid network topologies considered for WDM-PON networks. This contribution briefly deploys adequate Dynamic Wavelength Allocation (DWA) algorithms for selected WDM-PON network designs with the provision of traffic protection when only passive optical components in remote nodes are utilized. The main part of this study is focused on the use of wavelength scheduling methods for selected WDM-PON network designs. For evaluation of offline and online wavelength scheduling for novel hybrid network topologies, a simulation model realized in the Matlab programming environment allows to analyze interactions between various metropolitan and access parts in the Optical Distribution Network (ODN) related to advanced WDM-PON network designs. Finally, wavelength scheduling methods are compared from a viewpoint of utilization in advanced WDM-PON networks designs.

Core Function Prepositioning for Point-to-Point Service Slicing in Large-Scale Optical Networks

To accommodate three typical 5G services with satisfied performance requirements, spectrum slicing has been adopted and widely studied in the wireless transmission part. For the wired transmission part, the high-capacity and large-scale optical network is widely used for transferring 5G traffics. To improve the spectrum efficiency and reduce the time delay while accommodating 5G services, optical networks need to adapt to the wireless spectrum slicing. Traditionally, all spectrum resources in optical networks form a resource pool which is equally allocated to applications bit by bit until it is all used up. Although this pattern reduces the resource maintenance complexity, it has a high operation complexity for 5G services. If some important network functions are realized in advance, a 5G service can be easily deployed with simplified operations and satisfied performance requirements. In this letter, a novel framework of core function prepositioning is proposed to efficiently accommodate 5G services in optical networks. It adopts the centralized control model and two network functions of fast connection establishment and disaster-resilient survivability are realized in planned spectrum areas in advance. This framework adapts to the wireless spectrum slicing and has a significant performance boost while accommodating 5G services.

Multipath provisioning scheme for fault tolerance to minimize required spectrum resources in elastic optical networks

Multipath provisioning (MPP) uses multiple disjoint paths for data transmission to tolerate network failures. This paper proposes an MPP scheme, which allows allocating the different number of spectrum slots and different amount of transmission capacity to each path to minimize required spectrum resources in elastic optical networks. We present two optimization problems based on the proposed scheme and formulate them. Numerical results observe that the proposed scheme reduces the required spectrum resources compared to the conventional scheme, which allocates the same number of spectrum slots or the same amount of transmission capacity to each path.

WDM Network Issues: QOT Impairments, Dynamic Bandwidth Allocation, Modeling and Monitoring Schemes based on ML

Machine Learning (ML) has recently drawn the interest of both academics and professionals in the optical networking area to solve several problems. This trend has been triggered largely by the vast amount of available data (i.e., signal strength metrics, network alerts, etc.) and the large range of optimization criteria available in today's optical networks (such as modulation format, light path routes, transport wavelength, etc.). WDM systems are popular in the telecommunications industry. It increases network bandwidth without laying more cable. WDM technology in optical communication transports multiple optical carrier signals on a single fibre using various wavelengths of laser light. Wavelength division multiplexing (WDM) is an efficient strategy for leveraging the wide bandwidth of optical fibres to meet the rapid rise in demand for bandwidth on the Internet. WDM plays an essential role in both core and access networks in the communication network and faces various issues like its network performance is affected due to QoT impairments, Dynamic Bandwidth Allocation problem, Modeling, and Monitoring issues. Physical impairments are an issue in WDM and can cause calls to be blocked if the transmission quality is calculated in terms of minimum bit-error-rate. Dynamic allocation of bandwidth in WDM provides a crucial challenge for the effective and equal usage of the passive optical network upstream bandwidth when supporting the QoS specifications of various traffic groups. Fast attack monitoring can prevent the failure of vast volumes of data on all-optical networks. So, monitoring and modeling in a WDM network is also a critical issue. To solve these issues in WDM networks, more intelligence resources in scalable optical networks are necessary. ML techniques are demonstrating superiority in solving these issues. In this paper, a small detail about the WDM network is presented. Then, some WDM issues like QOT impairments, Dynamic Bandwidth Allocation, and modeling and monitoring are discussed, and then, in the next section focus on some ML techniques for solving these issues are presented.

Dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network

Aiming at the problem of dynamic multicast service protection in multi-domain optical network, this paper proposes a dynamic multicast sharing protection algorithm based on fuzzy game in multi-domain optical network. The algorithm uses the minimum cost spanning tree strategy and fuzzy game theory. First, it virtualizes two planes to calculate the multicast tree and the multicast protection tree respectively. Then, it performs a fuzzy game to form a cooperative alliance to optimize the path composition of each multicast tree. Finally, it generates a pair of optimal multicast work tree and multicast protection tree for dynamic multicast services. The time complexity of the algorithm is O(k3m2n), where n represents the number of nodes in the networks, k represents the number of dynamic multicast requests, and m represents the number of destination nodes for each multicast request. The experimental results show that the proposed algorithm reduces significantly the blocking rate of dynamic multicast services, and improves the utilization of optical network resources within a certain number of dynamic multicast request ranges.

On the Exploration of a Low-Power Photonic Network Architecture

The photonic on-chip network is an emerging technology that can provide low power and high bandwidth. However, photonic devices such as laser sources, resonators, and waveguides have high static power consumption, reducing the energy efficiency of the system. This article proposes a low-power optical network architecture. First, a dynamic network resource supply strategy is designed, and the optical network resources are adjusted according to the runtime traffic characteristics. Second, by leveraging power-efficient routers, our network architecture minimizes power used for compensating optical signal loss. Finally, an adaptive optical routing mechanism is designed to offer the lowest latency and power by utilizing existing network resources. The experimental results show that, compared to the existing scheme, our proposed architecture can save 51 percent power consumption and 60 percent energy consumption in the PARSEC and SPLASH-2 benchmark tests.

Wide-sense nonblocking multicast in WRMD WDM optical linear array and ring

Multicast communication is the simultaneous transmission of information from a single source to various destinations. It occurs extensively in telecommunication and advanced computing systems including enterprises operating datacenters. WDM optical networks act as the backbone for telecommunication and high performance networks. Wavelengths are scarce resources in WDM optical networks. Wavelengths usage in a network must be limited to decrease its cost and complexity. Optical linear array and ring networks find widespread application in interconnection networks including LAN and WAN. In this paper, wide-sense nonblocking multicast communication is analyzed in wavelength reusable multi-carrier distributed (WRMD) wavelength division multiplexing (WDM) linear array, unidirectional ring and bidirectional ring networks. The sufficient and necessary condition on the minimum wavelength number required for the network to be wide-sense nonblocking is derived for each of the above network topologies in the presence of a single multi-carrier light source (MCLS). An explicit wavelength allotment technique is also proposed for the above network topologies.

Joint balancing of IT and spectrum resources for selecting virtualized network function in inter-datacenter elastic optical networks.

With network functions decoupled from specific hardware, network function virtualization (NFV) is a promising technology to accelerate service provisioning in datacenter (DC) networks. In inter-datacenter elastic optical networks, each virtualized network function (VNF) is usually deployed in multiple DCs for the sake of survivability. In service provisioning, different VNF selections greatly affect IT resources in DCs as well as spectrum resources in optical networks. This paper investigates how to select appropriate VNFs for service requests to achieve joint load balancing of IT and spectrum resources. Two joint balancing factors are proposed to quantify the impact of different VNF selections on network load. Furthermore, a Joint-Optimization Selection (JOS) algorithm is designed to select VNFs in a joint load balancing manner. The performance of the proposed algorithm is evaluated in terms of resource utilization, blocking probability and average path length. Simulation results indicate that the proposed algorithm outperforms the benchmark algorithm.

Path-Based Fragmentation Metric and RSA Algorithms for Elastic Optical Networks

Flexi-grid technology has emerged as the evolution of fixed-grid DWDM core optical networks, enabling more efficient utilization of spectral resources and leading to higher overall network throughput. However, it suffers from an aggravated form of the spectrum fragmentation problem that affects fixed-grid networks. This work presents a novel path-based metric to better evaluate the fragmentation of spectral resources in flexi-grid optical networks, which considers that not all links of a path may contain enough free frequency slots and the likelihood that an end-to-end spectral void is large enough to house a connection. Furthermore, two families of heuristic routing and spectrum allocation (RSA) algorithms that preventively attempt to minimize the value of an input fragmentation metric are presented. These are used to evaluate the effectiveness of multiple metrics, both introduced in this work and from the existing literature, via simulations. We find that both proposed families can perform better, in terms of blocking probability and achievable network throughput, than the well-known K-shortest paths routing with a first fit spectrum allocation policy, with one of them trading performance for lower complexity, and that the proposed fragmentation metric outperforms the existing ones.