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Time-Wavelength Division Multiplexing Passive Optical Network (TWDM-PON) is considered as a promising solution of next generation PON (NG-PON). The integration of Edge Computing (EC) and TWDM-PON can satisfy the QoS requirements of delay-sensitive applications by providing storage, processing and caching capabilities at the network edge. However, with limited resource capacity, edge nodes in TWDM-PON are vulnerable to network attacks, e.g., Distributed Denial of Service (DDoS) attacks. Resource exhaustion in the attacked nodes easily leads to QoS degradation and even service blocking. This paper investigates how to effectively schedule traffic to mitigate the DDoS attack in EC-enabled TWDM-PON. Based on the collaboration of edge nodes, an adaptive traffic scheduling algorithm is designed to minimize the impact of DDoS attacks on delay sensitive services. The performance of the proposed algorithm is evaluated in simulation, where direct and indirect DDoS attacks are simulated. Besides, the attack duration and the number of attacked nodes are considered in the evaluation. Simulation results show that the proposed algorithm can effectively mitigate DDoS attacks in terms of reducing the QoS degradation rate and blocking rate of delay-sensitive services.

Quantum-key-distribution (QKD) enabled optical networks can provide secure keys for different kinds of applications to ensure the high security of communication processes. As the number of wavelength channels in a single-core fiber is limited, space division multiplexing (SDM) has been considered to be a valuable technique to provide more wavelength resources, which solves the problem of insufficient channel capacity. Due to the rapid expansion of data volume, the SDM-based QKD network has been regarded as an important paradigm. At the same time, resource allocation in multi-core optical networks is a problem worthy of studying. In this work, four routing, core, and wavelength allocation (RCWA) algorithms are proposed in the multi-core optical network for quantum service requests and classical service requests, which are referred to as RCWA without perception (RCWA-WP), RCWA with crosstalk perception (RCWA-XTP), RCWA with spectrum perception (RCWA-SP), and RCWA with core perception (RCWA-CP). Simulations are carried out to evaluate the network performance in terms of blocking probability, key utilization, and average crosstalk intensity. The comparative results indicate that the RCWA-SP algorithm can improve network performance and reduce the blocking probability, while the RCWA-XTP algorithm can reduce inter-core crosstalk during transmission.

With the increasing bandwidth requirements for people and the development of urbanization, the movement of the population in the city (especially the supercity) has an increasing influence on the traffic distribution in both space and time dimensions. The imbalanced distribution results in the regional blocking of different areas in different time periods and reduces the spectrum resource utilization in elastic optical networks. To resolve this problem, this paper proposes a tidal traffic model to formulate a kind of tidal traffic phenomenon firstly. Based on the analysis for this model, the area-aware routing and spectrum allocation algorithm that focuses on the traffic adjustment in specific functional areas is proposed. And two benchmark algorithms named min-hop k-shortest path routing algorithm and occupied-slots-as-weight k-shortest path routing algorithm are introduced. The evaluation results show that, compared to the benchmark algorithms, the proposed area-aware algorithm could reduce the blocking probability efficiently from 2% to 47% with low time complexity.

Network slicing is a key enabling technology to realize the provisioning of customized services in 5G paradigm. Due to logical isolation instead of physical isolation, network slicing is facing a series of security issues. Side Channel Attack (SCA) is a typical attack for slices that share resources in the same hardware. Considering the risk of SCA among slices, this paper investigates how to effectively allocate heterogeneous resources for the slices under their different security requirements. Then, a SCA-aware Resource Allocation (SCA-RA) algorithm is proposed for Ultra-reliable and Low-latency Communications (URLLC) and Enhanced Mobile Broadband (eMBB) slices in 5G RAN. The objective is to maximize the number of slices accommodated in 5G RAN. With dynamic slice requests, simulation is conducted to evaluate the performance of the proposed algorithm in two different network scenarios. Simulation results indicate that compared with benchmark, SCA-RA algorithm can effectively reduce blocking probability of slice requests. In addition, the usage of IT and transport resources is also optimized.

As an important bearer network of the fifth generation (5G) mobile communication technology, the optical transport network (OTN) needs to have high-quality network performance and management capabilities. Proof by facts, the combination of artificial intelligence (AI) technology and software-defined networking (SDN) can improve significant optimization effects and management for optical transport networks. However, how to properly deploy AI in optical networks is still an open issue. The training process of AI models depends on a large amount of computing resources and training data, which undoubtedly increases the carrying burden and operating costs of the centralized network controller. With the continuous upgrading of functions and performance, small AI-based chips can be used in optical networks as on-board AI. The emergence of edge computing technology can effectively relieve the computation load of network controllers and provide high-quality AI-based networks optimization functions. In this paper, we describe an architecture called self-optimizing optical network (SOON) with cloud-edge collaboration, which introduces control-layer AI and on-board AI to achieve intelligent network management. In addition, this paper introduces several cloud-edge collaborative strategies and reviews some AI-based network optimization applications to improve the overall network performance.

Physical layer authentication is an important way to ensure the security of optical communication network. We hereby propose a scheme to realize it by measuring the variation of the bit error rate (BER) on both sides of communication. In this scheme, the legitimacy of the receiver is identified by analyzing the BER variation of the optical fiber loop based on the short-term correlation of the channels. We then simulate a 16 PSK optical transmission system with intensity modulation direct detection-orthogonal frequency division multiplexing (IMDD-OFDM). The authentication effect is analyzed in the case of disturbance and beam split, as well as replacement of optical fiber channels caused by eavesdropper (Eve). The results show that this scheme is sensitive to the three kinds of attacks. A high probability of detection (PD) and a low false alarm rate (FAR) can be obtained. The experimental results show that with the increase of the frequency test, PD and FAR tend to be stable, and the authentication effect is better with the accuracy rate 100%.

The fast and diversified development of Internet services leads to numerous services with differentiated delay tolerance of optical connections set-up are converging in the optical network. Consequently, the average set-up delay of optical connection is increased, which will inevitably bring pressures to optical networks. To solve this problem, a delay aware routing spectrum assignment (RSA) algorithm based on services scheduling in priority queues with dynamic virtual topology construction (QVT-RSA) is proposed. First, the QVT-RSA algorithm reasonably identifies various different services and arranges them in order according to their priority, waiting time and delay tolerance requirements. Then, software defined networks (SDN) controller with multi-threads technology is adopted to innovatively parallel serve the ordered service requests to reduce the average set-up delay of optical connections, which also offset the induced delay caused by services scheduling. The network resource is accurately shared among multi-threads using the proposed mutual exclusive resource utilization model realized by dynamic virtual topology construction. The continuously coloring and usable virtual topology linkage reconfiguration can provide topology resources for service requests and adapt the dynamic transformation among serving, waiting and new arriving service requests. The shortest-path routing and first fit spectrum assignment (SPFF-RSA) algorithm is used as the baseline algorithm. Furthermore, by combining the SPFF-RSA algorithm and partial strategy of our strategy, the QSPFF-RSA and V-RSA algorithms are proposed as baseline algorithms as described in V-B. The simulation experiment results demonstrate that the average optical connections set-up delay of QVT-RSA algorithm is reduced compared with SPFF-RSA and QSPFF-RSA algorithms, and the blocking probability of QVT-RSA algorithm is reduced compared with SPFF-RSA, QSPFF-RSA and VRSA algorithms. The optical connections set-up success probability within delay tolerance about high, medium and low priority services of QVT-RSA algorithm is higher than that of the SPFF-RSA, QSPFF-RSA and VRSA algorithms.

Quantum key distribution (QKD) has attracted much attention on secure communications across global networks. QKD over satellite networks can overcome the limitations of terrestrial optical networks, such as large attenuation over long distance fiber channel and difficulty of intercontinental domain communications. Different QKD networks (around the world) can intercommunicate through quantum satellites, leading to a global quantum network in near future. This raises a new resource allocation and management problem of QKD involving multiple satellite layers and distributed ground stations. Using existing schemes, a single satellite cannot perform QKD for ground stations for the whole day. Moreover, the research problem is more challenging due to limitations of satellite coverage: limited cover time of low earth orbit (LEO) satellite, high channel losses of geostationary earth orbit (GEO) satellite, etc. To overcome these limitations, our study proposes a double-layer quantum satellite network (QSN) implemented quantum key pool (QKP) to relay keys for ground stations. We propose a new architecture of trusted-repeater-based double-layer quantum satellite networks, comprising GEO and LEO satellites. We also address the routing and key allocation (RKA) problem for key-relay services over QSNs. We propose a novel joint GEO-LEO routing and key allocation (JGL-RKA) algorithm to solve the RKA problem. Simulative results show that the proposed scheme can increase success probability of key-relay services significantly. We also present the impact of different route selections mechanisms, number of satellite links, satellite node capability, and service granularity on network performance.

Quantum key distribution (QKD) promises to deliver secure keys, which can be applied for security demands in optical networks by using cost-efficient and scalable lightpaths. To achieve such secure communication, the QKD integrated with optical networks has become a promising scenario to provide key provisioning services in optical networks. As an inevitable problem, the occurrence of failures becomes a challenge for the resiliency of the network. In that context, this paper studies the resilient QKD-integrated optical networks against single link failure. By analyzing and quantifying the key provisioning services, we constructed the secret-key flow model (SKFM) for the failure-affected and failure-unaffected cases. Based on the SKFM, a secret-key recovery strategy (SKRS) including three algorithms (i.e., one-path recovery method (OPRM), multi-path recovery method (MPRM), and time window-based recovery method (TWRM)) is designed to recover failure-affected key provisioning services in the network. The simulation work has been conducted to evaluate the performance of OPRM, MPRM, and TWRM in terms of key-service recovery ratio, secret-key recovery ratio, wavelength consumption ratio, and secret-key consumption ratio. Numerical results show that the three algorithms can recover failure-affected key provisioning services effectively, i.e., the MPRM outperforms the OPRM and the TWRM outperforms the MPRM. Better recovery can be realized by sacrificing more wavelength and secret-key resources, which are also required for the delivery of the QKD in the network. Thus, a trade-off can be achieved between the recovery of key provisioning services and the delivery of the QKD on wavelength resources and secret-key resources.

As a concept to enhance and extend cloud-computing capabilities, edge computing aims to provide Internet-based services in the close proximity to users by placing IT infrastructures at the network edge in forms of tiny datacenters. Taking advantage of the close distance to end user and access networks, edge datacenters can provide low-latency and context-aware services and further improve users' quality of experience. As the network edge is a geographically spread concept, the edge datacenters are usually highly distributed so that they can provide nearby storage and processing capabilities to most of the end users. Furthermore, edge datacenters also co-work with centralized cloud datacenters for service orchestration. Such decentralization and collaboration are expected to introduce significant transformations to both infrastructures and applications. To provide an overview of how edge can be integrated with cloud-computing and how edge computing can benefit applications, this paper studies the infrastructure and application issues of edge computing and networking in several sub-aspects, including related concepts, infrastructures, resource management and virtualization, performance, and applications.

This paper proposes a novel key distribution system based on the measurement of the bit error rate (BER) in a fiber channel. By carrying out the loopback BER measurement at both the transmitting and the receiving end, the BER is quantified and codified to generate consistency keys. Alice and Bob respectively encrypt the signal with the help of the public key base at the transmitting end. At the receiving end the data are decrypted and then the BER is measured. The security of generated keys in the system is enhanced by the use of the encryption base and the randomness of the channel. Additionally, noise sources are added to the channel so that the random noise conceals signals and Eve cannot eavesdrop the useful information in it. Due to the randomness of the channel noise, the generated keys have good randomness. This system at a high key generation rate is compatible with the existing communication device and its measurement is simple. The 10G bit/s-200 km coherent optical communication system is used to measure the BER of the security feature information of the extracted channel. The experimental results show that the key distribution system obtains a consistency rate of 98% with the key generation rate 2 Mbps, both of which have been significantly improved.

Achievable capacity of optical fiber is approaching its physical limitation in frequency domain. Space division multiplexing (SDM) technology can scale the network capacity using multi-core fiber and multi-mode fiber. In order to provide high-speed transmission services with fine granularities, SDM enabled elastic optical networks (SDM-EONs) become a promising candidate of future optical transport networks. However, since the spectrum status in SDM-EONs becomes more complex with the introduction of spatial dimension, the issue of spectrum fragmentation will be more serious in SDM-EONs compared in simple EONs. To remedy the issue of spectrum fragmentation in SDM-EONs, we propose a crosstalk-aware spectrum defragmentation (CASD) algorithm based on a metric, i.e., spectrum compactness (SC), which we define to measure the spectrum status in the SDM-EONs. Simulation results show that the proposed CASD algorithm can achieve better performance than a benchmark algorithm in terms of blocking probability and spectrum utilization. We also compare CASD algorithm with different SC thresholds in bandwidth blocking probability and spectrum utilization. Among them, CASD algorithm with SC threshold of 50 performs the best. It can achieve low spectrum moving times as well as low defragmentation latency.

Driven by the development of cloud computing and mobile Internet, network-based applications have become diverse. Besides the usual immediate reservation (IR) applications, which need to be served immediately, advance reservation (AR) applications have been introduced to support initial-delay-tolerance services, such as grid computing, virtual machine backup, and so on. The provisioning mechanism of AR applications is different from that of IR applications, because AR requests don't require to be served immediately, and the network operator must decide the exact serving time in the AR service provisioning process. Based on the scheduling features of AR requests, this paper formulates a resource model and sets up a control framework for elastic optical networks to support AR services. We propose an optimization algorithm with three reprovisioning policies to dynamically reprovision the AR applications, which have already been scheduled. Both the proposed control framework and algorithm are developed on the basis of an open network operating system, which is an open-source software-defined networking controller. Also, the performance of the proposed algorithm is evaluated via software simulation. Demonstration results show the benefits of reprovisioning, and simulation results show that the reprovisioning optimization algorithm can improve the efficiency of network spectrum resource.

Inter-datacenter services such as data replication and virtual machine migration contribute significantly to the underlying network traffic. These bulk-data transfer services can tolerate certain delay if the completion time is guaranteed with a pre-defined deadline. In this paper, we propose joint frequency and time-domain optimization algorithms of static routing and spectrum assignment (RSA) for these deadline-driven bulk-data transfer requests in elastic optical networks. We formulate the problem as an integer linear program (ILP) and then propose six scheduling schemes, which combine three request ordering strategies with two RSA algorithms. Simulation results show that compared with ILP, our schemes can achieve the same performance in terms of spectrum utilization with efficient time complexity. Furthermore, based on the numerical results and computational efficiency, we provide a guideline on choosing scheduling schemes.