Jun Li

To satisfy the stringent requirements of emerging broadband services in home networks, a novel Centralized optical and Wi-Fi Access Network (C-WAN) has been proposed within the context of Fiber-to-The-Room (FTTR). In C-WAN, centralized management and control of multiple Wi-Fi access points (APs) deployed in each room are facilitated by relocating portions of Wi-Fi protocols from the APs to a centralized entity. This approach significantly enhances network performance, including throughput and roaming capabilities. However, C-WAN also imposes strict demands on the fronthaul networks, specifically requiring high bandwidth and ultra-low latency. In this context, orthogonal frequency division multiplexing passive optical network (OFDM-PON) emerges as a promising solution to support the C-WAN fronthaul network by allocating dedicated subcarriers to each AP. In C-WAN over OFDM-PON, Wi-Fi stations still contend for access to the wireless channel based on existing Wi-Fi protocols, which may result in prolonged wireless access delays. Consequently, the Quality of Service (QoS) requirements for time-sensitive (TS) services may not be met. Additionally, the variation in maximum Wi-Fi throughput due to the contention-based access mechanism presents a significant challenge for the efficient allocation of optical network resources under stringent delay constraints. To address these issues, we propose a priority-based access mechanism that assigns higher priority to TS services for accessing Wi-Fi channels and obtaining wireless resources. Building on this mechanism, we further develop a Wi-Fi throughput prediction model, which is used to optimize the allocation of optical network resources. Simulation results demonstrate that the proposed scheme can effectively reduce wireless access delay and jitter for TS services, meeting their performance requirements while also improving the utilization of optical network resources.

Traditional standard single-mode fibers (SSMF) are unable to satisfy the future long-distance and high-speed optical channel transmission requirement due to their relatively large signal losses. To address this issue, the ultra-low loss and large effective area (ULL) fibers are successfully manufactured and expected to deployed in the existing optical networks. For such ULL fiber deployment, network operators prefer adding ULL fibers to each link rather than replace existing SSMFs, resulting in a scenario where both of SSMF and ULL fiber coexist on the same link. In this paper, we investigated the routing, fiber, modulation format, and spectrum allocation (RFMSA) problem in the context of an elastic optical network (EON) where ULL fiber and SSMF coexisting on each link under both the static and dynamic traffic demands. We formulated this RFMSA problem as a node-arc based Mixed Integer Linear Programming (MILP) model and developed Spectrum Window Plane (SWP)-based heuristic algorithms based on different fiber selection strategies, including spectrum usage based (SU), optical signal-to-noise ratio (OSNR) aware, ULL fiber first (UFF), and random strategies. Simulation results show that in the static traffic demand situation, the RFMSA algorithm based on the OSNR-aware (OA) strategy exhibits optimal performance, attaining a performance similar to that of the MILP model regarding the maximum number of frequency slots (FSs) used in the entire network. Moreover, in the dynamic traffic demand scenario, the SU strategy remarkably surpasses the other strategies in terms of the lightpath blocking probability.

With the rapid growth of Internet traffic and new services, demands on access network bandwidth and latency have intensified. Fiber-to-the-Room (FTTR) has emerged as a new architecture for indoor networks, extending fiber directly to users via optical edge gateways. Despite FTTR’s performance benefits, concerns about its equipment’s power consumption have been overlooked. This study investigates FTTR-based home networks, developing models for device power consumption and energy use over time. Results indicate higher power consumption required by FTTR-based networks compared to traditional Wi-Fi networks. To mitigate this, we propose leveraging FTTR’s centralized control for an innovative energy-saving mechanism, enhancing network efficiency and reducing overall energy consumption. Additionally, we explore integrating millimeter-wave technology to further boost energy efficiency through increased transmission capacity.

Integrated sensing and communication (ISAC) systems traditionally presuppose that sensing and communication (S&C) channels remain approximately constant during their coherence time. However, a “DISCO” reconfigurable intelligent surface (DRIS), i.e., an illegitimate RIS with random, time-varying reflection properties that acts like a “disco ball”, introduces a paradigm shift that enables active channel aging more rapidly during the channel coherence time. In this letter, we investigate the impact of DISCO jamming attacks launched by a DRIS-based fully-passive jammer (FPJ) on an ISAC system. Specifically, an ISAC problem formulation and a corresponding waveform optimization are presented in which the ISAC waveform design considers the trade-off between the S&C performance and is formulated as a Pareto optimization problem. Moreover, a theoretical analysis is conducted to quantify the impact of DISCO jamming attacks. Numerical results are presented to evaluate the S&C performance under DISCO jamming attacks and to validate the derived theoretical analysis.

In the 5G and beyond 5G networks, achieving security-aware data transmission needs to convert clients ’ requests into a service function chain (SFC), each service function (SF) providing a certain security guarantee. With diverse configuration techniques, an SF may own multiple versions, each version providing various security guarantees with diverse costs. It should be notice that, as the recent software failures have caused severe financial loss, great attentions from both academia and industry have been put onto the SFC reliability. In the literature, existing works have solely investigated the following two fields: 1) how to deploy a security-aware SFC, and 2) how to protect a traditional SFC. Simply applying these techniques to dealing with the problem of security-aware SFC protection might not be efficient as the backup and primary SFCs may not be identical for security-aware SFCs. Therefore, how to jointly take these fields into account is challenging and remains open. To tackle the above problem, this paper studies how to construct and embed a security-aware SFC with asymmetric dedicated protection. We mathematically define this problem and name it security-aware service function chaining, embedding, and protection with multi-versioned SFs (SFCEP-MF) with the objective of cost optimization. Next, to optimize the SFCEP-MF problem, we construct an efficient algorithm, called augmenting-path with primary-first disjoint SFP identifier (APPF-DSI). Extensive simulation results show that the APPF-DSI algorithm outperforms the benchmark approaches that are directly extended from the state-of-the-art.

10-Gbps symmetrical passive optical network (XGS-PON) and Wi-Fi 6 are two key technologies to provide gigabit access for the fifth-generation fixed network (F5G). However, how to integrate XGS-PON and Wi-Fi 6 to meet F5G’s stringent quality of service requirements is still a challenge. In this letter, we propose a cooperative resource scheduling scheme, in which a communication tunnel is established to achieve a low end-to-end (E2E) delay by sharing medium access control information between XGS-PON and Wi-Fi 6. Simulation results show that the proposed scheme can significantly reduce the E2E delay for time-sentinel services by up to 50% without sacrificing the performance of non-time-sensitive services.

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.

This chapter presents a fog computing enabled cellular network (FeCN), in which the high user-mobility feature brings critical challenges for service continuity under stringent service requirements. Service migration is promising to fulfill the service continuity during mobility. However, service migration cannot be completed immediately and may lead to situations where the user-experience degrades. For this, a quality-of-service aware service migration strategy is proposed. The method is based on existing handover procedures with newly introduced distributed fog computing resource management scheme to minimize the potential negative effects induced by service migration. The performance of the proposed schemes is evaluated by a case study, where realistic vehicular mobility pattern in the metropolitan network of Luxembourg is used. Results show that low end-to-end latency for vehicular communication can be achieved. During service migration, both the traffic generated by migration and the other traffic (e.g., control information, video) are transmitted via mobile backhaul networks. To balance the performance of the two kinds of traffic, a delay-aware bandwidth slicing scheme is proposed. Simulation results show that, with the proposed method, migration data can be transmitted successfully within a required time threshold, while the latency and jitter for nonmigration traffic with different priorities can be reduced significantly.

The emergence of edge computing provides an effective solution to execute distributed model training (DMT). The deployment of training data among edge nodes affects the training efficiency and network resource usage. This letter aims for the efficient provisioning of DMT services by optimizing the partition and distribution of training data in edge computing-enabled optical networks. An integer linear programming (ILP) model and a data parallelism deployment algorithm (DPDA) are proposed to solve this problem. The performance of the proposed approaches is evaluated through simulation. Simulation results show that the proposed algorithm can deploy more DMT services compared with benchmark.