Search Results (30)

With the advent of 6G technologies, satellite communication networks are in urgent need of innovative bearer technologies to meet the demands of government and enterprise private lines as well as computing power networks. We propose optical service unit-based optical inter-satellite links (OISL-OSU) as a solution to address the current limitations in fine-grained service bearing within optical transport networks (OTNs), thereby enhancing the flexibility and efficiency of satellite optical networks. Comparative tests were conducted between OISL-OSU and existing packet-switching technologies in multi-service satellite optical transport networks. Through hardware-in-the-loop simulation verification, key performance indicators such as delay optimization, bandwidth utilization rate, and flexible resource adjustment capability were systematically evaluated. Experimental results demonstrate that OISL-OSU technology exhibits superior performance in delay optimization and fine-grained service bearing. The flexible mapping and multiplexing mechanism of OISL-OSU significantly improves resource utilization efficiency, decreases transmission delay, and strengthens hard-pipe connection capabilities. Full article

This paper discusses modern approaches to the creation of a highly reliable data transmission system for unmanned surface vehicles (USVs) operating under interference conditions. In contrast to existing solutions, an improved communication algorithm is proposed to ensure uninterrupted transmission of video, telemetry, and control signals even in highly unstable environments. The study identifies the main technical requirements for data transmission and evaluates the key parameters of the communication channel. The proposed hybrid communication system utilizes adaptive channel switching, data compression, and equipment reconfiguration, improving data transmission stability and reducing latency. A comparative analysis of existing communication technologies reveals the limitations of acoustic, optical, and radio wave systems. A conceptual architecture combining these technologies provides optimal data transmission by adapting to the environment. Experimental results confirm the effectiveness of the system, demonstrating reliable operation even with 80% packet loss in public Internet networks. The system’s adaptability, low latency, and dynamic routing make it suitable for real-time USV operations, including environmental monitoring, scientific research, and search and rescue missions. Its potential extends to commercial and dual applications requiring sustained data transmission in challenging maritime environments. Full article

Optical burst switching (OBS) is a network architecture that combines the advantages of packet and circuit switching techniques. However, OBS networks are susceptible to cyber-attacks, such as flooding attacks, which can degrade their performance and security. This paper introduces a novel machine learning method for flooding attack detection in OBS networks, based on a third-order distance function for k-nearest neighbors (KNN3O). The proposed distance is expected to improve detection accuracy due to higher sensitivity with respect to the distance difference between two points. The developed method is compared with seven other machine learning methods, namely standard KNN, KNN with cosine distance (KNNC), multi-layer perceptron (MLP), naive Bayes classifier (NBC), support vector machine (SVM), decision tree (DT), and discriminant analysis classifier (DAC). The methods are further assessed using five metrics: accuracy, precision, recall, F1-score, and specificity. The proposed method achieved an accuracy of 99.3%, outperforming the original KNN, MLP, and SVM, which achieved accuracies of 99%, 76.4%, and 94.7%, respectively. The results show that KNN3O is the best method for flooding attack detection in OBS networks, as it achieves the highest scores in all five metrics. Full article

Current trends in network traffic management rely on the efficient control of individual flows. Software-defined networking popularized this notion. Per-flow management is perfectly viable in standard IP networks, in which packet processing is in the electric domain. However, optical networks provide more restrictions and constraints making per-flow traffic management difficult. One of the most important challenges is to reduce the concurrent number of flows present in the flow tables to make the switching process quicker. In this paper, we propose a mechanism to manage flow timeout values that uses idle timeout and hard timeout parameters. To calculate the appropriate values of the parameters, the mechanism analyzes the packet inter-arrival times. The algorithm also takes into account the current occupancy of the flow table. Full article

In this paper, the operating characteristic curves (OCCs) of optical code-division multiplexing (OCDM) technology for label switching of an optical packet-switching (OPS) network was evaluated. A node structure for processing the packets, with spectral-amplitude-coding (SAC) labels, considering a balanced detector and an optical switch, was developed and modeled. The effects of decoding noises on the performance of both M-sequence and stuffed quadratic congruence (SQC) labeling systems were addressed. Hypothesis testing was applied to the decoder to investigate the results of label recognition. The null and alternative hypotheses were, respectively, defined as a decoder receiving the matching and mismatching labels. Due to the noise effects, the decoder output may not reflect the label status correctly. Type I error occurs when the null hypothesis is true while accepting the alternative one. Type II error occurs when the alternative hypothesis is true while accepting the null one. Analytic equations of both errors were given, considering a desired packet that was missed and an undesired packet shown in a switched path. The trade-off between these two errors, regarding the decoder threshold, was demonstrated in operating characteristic curves (OCCs). A better OCC could be found when a packet had more labeled payload bits, or when the utilized label code had a lower auto-to-cross-correlation ratio. Full article

This work concentrates on the problem of optimizing the cost of a passive wavelength division multiplexing (WDM) optical network used as a transport network for carrying the xHaul packet traffic between a set of remote radio sites and a central hub in a 5G radio access network (RAN). In this scope, we investigate the flexible use of optical add-drop multiplexers (OADMs) for the aggregation of traffic from a number of remote sites, where the type/capacity of optical devices—OADMs and optical multiplexers (MUXs)—is selected in accordance with the traffic demand. The approach is referred to as Flex-O. To this end, we formulate the xHaul network planning problem consisting in the joint provisioning of transmission paths (TPs) between the remote sites and the hub with optimized selection and placement of OADMs on the paths and proper selection of MUXs at the ends of the TPs. The problem formulation takes into accounts the optical power budget that limits the maximum transmission distance in a function of the amount and type of optical devices installed on the TPs. The network planning problem is modeled and solved as a mixed-integer linear programming (MILP) optimization problem. Several network scenarios are analyzed to evaluate the cost savings from the flexible (optimized) use of OADMs. The scenarios differ in terms of the availability of OADMs and the capacity of the WDM devices applied on the TPs. The numerical experiments performed in three mesh networks of different size show that the cost savings of up to between 35 and 45% can be achieved if the selection of OADMs is optimized comparing to the networks in which either single-type OADMs are used or the OADMs are not applied. Full article

In this paper, we investigate the three-stage, wavelength–space–wavelength switching fabric architecture for nodes in elastic optical networks. In general, this switching fabric has r input and output switches with wavelength-converting capabilities and one center-stage space switch that does not change the spectrum used by a connection. This architecture is most commonly denoted by the WSW1 (r, n, k) switching network. We focus on this switching fabric serving simultaneous connection routing. Such routing takes place mostly in synchronous packet networks, where packets for switching arrive at the inputs of a switching network at the same time. Until now, only switching fabrics with up to three inputs and outputs have been extensively investigated. Routing in switching fabrics of greater capacity is estimated based on routing in switches with two or three inputs and outputs. We now improve the results for the switching fabrics with four inputs and outputs and use these results to estimate routing in the switching fabric with an arbitrary number of inputs and outputs. We propose six routing algorithms based on matrix decomposition for simultaneous connection routing. For the proposed routing algorithms, we derive criteria under which they always succeed. The proposed routing algorithms allow the construction of nonblocking switching fabrics with a lower number of wavelength converters and the reduction of the overall switching fabric cost. Full article

Aiming at providing a high-performance terrestrial network for edge computing in satellite networks, we experimentally demonstrate a high bandwidth and low latency decomposed optical computing architecture based on distributed Nanoseconds Optical Switches (NOS). Experimental validation of the decomposed computing network prototype employs a four-port NOS to interconnect four processor/memory cubes. The SOA-based optical gates provide an ON/OFF ratio greater than 60 dB, enabling none-error transmission at a Bit Error Rate (BER) of 1 × 10⁻⁹. An end-to-end access latency of 122.3 ns and zero packet loss are obtained in the experimental assessment. Scalability and physical performance considering signal impairments when increasing the NOS port count are also investigated. An output OSNR of up to 30.5 dB and an none-error transmission with 1.5 dB penalty is obtained when scaling the NOS port count to 64. Moreover, exploiting the experimentally measured parameters, the network performance of NOS-based decomposed computing architecture is numerically assessed under larger network scales. The results indicate that, under a 4096-cube network scale, the NOS-based decomposed computing architecture achieves 148.5 ns end-to-end latency inside the same rack and zero packet loss at a link bandwidth of 40 Gb/s. Full article

In order to meet the massively increasing requirements of big-data applications, data centers (DCs) are key infrastructures to cope with the associated demands, such as high performance, easy scalability, low cabling complexity and low power consumption. Many research efforts have been dedicated to traditional wired data center networks (DCNs). However, DCNs’ static and rigid topology based on optical cables significantly limits their flexibility, scalability, and even reconfigurability. The limitations of this wired connection can be addressed with optical wireless technology, which avoids cable complexity problems while allowing dynamic adaption and fast reconfiguration. Here, we propose and investigate a novel optical wireless data-center network (OW-DCN) architecture based on nanoseconds semiconductor optical amplifier (SOA)-based wavelength selectors and arrayed waveguide grating router (AWGR) controlled by fast field-programmable gate array (FPGA)-based switch schedulers. The full architecture, including the design, packet-switching strategy, contention solving methodology, and reconfiguration capability, is presented and demonstrated. Dynamic switch scheduling with a FPGA-based switch scheduler processing optical label and software-defined network (SDN)-based reconfiguration were experimentally confirmed. The proposed OW-DCN was also achieved with a power penalty of less than 2 dB power penalty at BER < 1 × 10⁻⁹ for a 50 Gb/s OOK transmission and packet-switching transmission. Full article

One of the main challenges in dense 5G radio access networks (RANs) is provisioning of low-cost connectivity between a large number of antennas, located at remote sites, and a central site (hub) in which baseband processing functions are performed. Packet-switched Ethernet and wavelength division multiplexing (WDM) are two principal transport network technologies enabling the reduction of the demand for direct optical fiber connections between the antennas and the hub. Whereas Ethernet allows for statistical multiplexing of multiple xHaul (fronthaul/midhaul/backhaul) flows and their aggregation in a high-capacity transmission link, WDM makes it possible to establish a number of such links (using different wavelengths) in a single optical fiber. Additional savings in the amount of fibers required can be achieved by means of optical add-drop multiplexers (OADMs) that allow for obtaining access to unused wavelengths by intermediate remote nodes, whenever the capacity on the WDM system is not fully utilized by the end remote node. In this work, we focus on the problem of planning optimal fiber connections, including the placement of OADMs for a set of wavelength demands at remote sites, with the aim of minimizing the amount of fibers used in a packet-optical xHaul access network carrying 5G traffic. We consider a passive WDM system in which the maximum transmission distance, estimated using an optical power-budget model, depends on the number of OADMs that are present on the transmission path. To formulate and solve the optimization problem, we make use of integer linear programming (ILP). We apply the ILP model in network analysis. In particular, by means of numerical experiments performed for two different network topologies, we study the impact of traffic load (in terms of the number of requested wavelengths) and optical multiplexer loss on the number of transmission paths that have to be established in the network. Obtained results show that the savings in fiber connections of up to $65\%$ can be achieved in a packet-optical xHaul network if OADMs are used when compared to the scenario without OADMs. Full article

An Optical Burst Switching (OBS) network is vulnerable to Burst Header Packet (BHP) flooding attack. In flooding attacks, edge nodes send BHPs at a high rate to reserve bandwidth for unrealized data bursts, which leads to a waste of bandwidth, a decrease in network performance, and massive data loss. Machine learning techniques are utilized to detect this attack in the OBS network. In this paper, we propose a particle swarm optimization–support vector machine (PSO-SVM) model for detecting BHP flooding attacks, in which the PSO is used to optimize the parameters of the SVM. We use the dataset provided by the UCI warehouse to train and test the model. The experimental results show that the detection accuracy of the PSO-SVM model reaches 95.0%, which is 9.4%, 9.6%, 20.7%, 8% higher than naïve Bayes, SVM, k-nearest neighbor, and decision tree. Although DCNN outperforms our model, it requires more processing and training time. Collectively, our approach is effective and high-efficiency in detecting flooding attacks in optical burst switching networks and maintaining network stability and security. Full article

In this paper, we propose a novel optical packet switch (OPS) architecture with input concentrators, which employ multi-input single-output optical buffers to aggregate all the incoming traffic into a small size switching fabric. Accordingly, the physical size, the number of the needed wavelength converters, and the economic cost of the total OPS node are decreased dramatically. However, the deployment of input concentrators introduces additional packet loss and delay, except from the contention at the switch output. A Markov model is presented to study the packet loss ratio (PLR) and average packet delay given by the input concentrators. The corresponding closed form expressions are given. The model also demonstrates that the system performance can be greatly improved by increasing the buffer size when the traffic load is not larger than 0.69315. The analytical values are compared with the simulation results. All the obtained results show that the proposed model provides satisfactory approximations under different network scenarios. Moreover, the economic cost savings of the proposed OPS node at the present time and its evolution as a function of time are also discussed in detail. The proposed architecture can also be applied in a packet enhanced optical transport network (OTN). Full article

This paper presents a comparative analysis of four semi-supervised machine learning (SSML) algorithms for detecting malicious nodes in an optical burst switching (OBS) network. The SSML approaches include a modified version of K-means clustering, a Gaussian mixture model (GMM), a classical self-training (ST) model, and a modified version of self-training (MST) model. All the four approaches work in semi-supervised fashion, while the MST uses an ensemble of classifiers for the final decision making. SSML approaches are particularly useful when a limited number of labeled data is available for training and validation of the classification model. Manual labeling of a large dataset is complex and time consuming. It is even worse for the OBS network data. SSML can be used to leverage the unlabeled data for making a better prediction than using a smaller set of labelled data. We evaluated the performance of four SSML approaches for two (Behaving, Not-behaving), three (Behaving, Not-behaving, and Potentially Not-behaving), and four (No-Block, Block, NB- wait and NB-No-Block) class classifications using precision, recall, and F1 score. In case of the two-class classification, the K-means and GMM-based approaches performed better than the others. In case of the three-class classification, the K-means and the classical ST approaches performed better than the others. In case of the four-class classification, the MST showed the best performance. Finally, the SSML approaches were compared with two supervised learning (SL) based approaches. The comparison results showed that the SSML based approaches outperform when a smaller sized labeled data is available to train the classification models. Full article

In this paper, an optical buffering solution based on label switching is proposed, where packets are buffered by identifying and renewing the light labels of pseudo-orthogonal codes. The buffer overflow occurs when label switching fails to perform on the queued packets due to the insufficient labels. Assigning an increased code number to the buffer could reduce the overflow effect, but the decoder noise mitigates its efficiency. Therefore, we study a noise-immune labeling method of residual function by advancing the correlation properties of the existing codes. The proposed label-switching scheme improves the solution efficiency to buffer overflow as a lower code-error probability can be reached. Moreover, multiple label codes can be simultaneously generated from a shared light source to achieve a power-efficient buffer structure. Full article

The deployment of new 5G services and future demands for 6G make it necessary to increase the performance of access networks. This challenge has prompted the development of new standardization proposals for Passive Optical access Networks (PONs) that offer greater bandwidth, greater reach and a higher rate of aggregation of users per fiber, being Time- and Wavelength-Division Multiplexing (TWDM) a promising technological solution for increasing the capacity by up to 40 Gbps by using several wavelengths. This solution introduces tunable transceivers into the Optical Network Units (ONUs) for switching from one wavelength to the other, thus addressing the ever-increasing bandwidth demands in residential broadband and mobile fronthaul networks based on Fiber to the Home (FTTH) technology. This adds complexity and sources of inefficiency, such as the laser tuning time (LTT) delay, which is often ignored when evaluating the performance of Dynamic Bandwidth Allocation (DBA) mechanisms. We present a novel DBA algorithm that dynamically handles the allocation of bandwidth and switches the ONUs’ lasers from one wavelength to the other while taking LTT into consideration. To optimize the packet delay, we introduce a scheduling mechanism that follows the Longest Processing Time first (LPT) scheduling discipline, which is implemented over the Interleaved Polling with Adaptive Cycle Time (IPACT) DBA. We also provide quality of service (QoS) differentiation by introducing the Max-Min Weighted Fair Share Queuing principle (WFQ) into the algorithm. The performance of our algorithm is evaluated through simulations against the original IPACT algorithm, which we have extended to support multi-wavelengths. With the introduction of LPT, we obtain an improved performance of up to 73% reduction in queue delay over IPACT while achieving QoS differentiation with WFQ. Full article