Control Layer Research Articles

Biodistribution and function of coupled polymer-DNA origami nanostructures

Spatial control over the distribution of therapeutics is a highly desired feature, which could limit the side effects of many drugs. Here we describe a nanoscale agent, fabricated from a coupled polymer-DNA origami hybrid that exhibits stability in serum and slow diffusion through tissues, in a manner correlating with shape and aspect ratio. Coupling to fragments of polyethylene glycol (PEG) through polyamine electrostatic interactions resulted in marked stability of the agents in-vivo, with > 90% of the agents maintaining structural integrity 5 days following subcutaneous injection. An agent functionalized with aptamers specific for human tumor necrosis factor TNF-alpha, significantly abrogated the inflammatory response in a delayed-type hypersensitivity model in humanized TNF-alpha mice. These findings highlight polymer-DNA hybrid nanostructures as a programmable and pharmacologically viable update to mainstream technologies such as monoclonal antibodies, capable of exerting an additional layer of control across the spatial dimension of drug activity.

Exportin-mediated nucleocytoplasmic transport maintains Pch2 homeostasis during meiosis.

The meiotic recombination checkpoint reinforces the order of events during meiotic prophase I, ensuring the accurate distribution of chromosomes to the gametes. The AAA+ ATPase Pch2 remodels the Hop1 axial protein enabling adequate levels of Hop1-T318 phosphorylation to support the ensuing checkpoint response. While these events are localized at chromosome axes, the checkpoint activating function of Pch2 relies on its cytoplasmic population. In contrast, forced nuclear accumulation of Pch2 leads to checkpoint inactivation. Here, we reveal the mechanism by which Pch2 travels from the cell nucleus to the cytoplasm to maintain Pch2 cellular homeostasis. Leptomycin B treatment provokes the nuclear accumulation of Pch2, indicating that its nucleocytoplasmic transport is mediated by the Crm1 exportin recognizing proteins containing Nuclear Export Signals (NESs). Consistently, leptomycin B leads to checkpoint inactivation and impaired Hop1 axial localization. Pch2 nucleocytoplasmic traffic is independent of its association with Zip1 and Orc1. We also identify a functional NES in the non-catalytic N-terminal domain of Pch2 that is required for its nucleocytoplasmic trafficking and proper checkpoint activity. In sum, we unveil another layer of control of Pch2 function during meiosis involving nuclear export via the exportin pathway that is crucial to maintain the critical balance of Pch2 distribution among different cellular compartments.

Research on control strategy of distributed photovoltaic cluster based on improved particle swarm-gray wolf coupling algorithm

Conducting research on cluster control strategies for distributed photovoltaic systems to address voltage fluctuations and reverse power flow caused by large-scale distributed photovoltaic integration is crucial foundational work in establishing a new power system and ensuring its safe and stable operation. Based on the division of distributed photovoltaic cluster, this paper takes distributed photovoltaic cluster as the intermediate layer of control, and researches the two-layer control strategy of inter-cluster coordination and intra-cluster autonomy. The inter-cluster coordination strategy is located at the upper layer, and this strategy based on the power grid structure of the controlled area, comprehensively considering the observability, controllability, degree and betweenness centrality of each node, the latter two characterize the spatial location of the nodes. The dominant nodes of each cluster are selected by the above multiple indicators. The multi-objective inter-cluster coordination control model respectively focusing on the minimum voltage deviation of the dominant node or the minimum network loss of the system is constructed according to whether the voltage of the dominant node crosses the limit or not, and the improved particle swarm-gray wolf coupling algorithm (PSO-GWO) is used to generate the output indicators of each cluster. The intra-cluster autonomy strategy is at the lower layer. In the shortage of adjustable PV resources connected to the dominant node, the intra-cluster autonomy strategy adopting the control sequence of dominant node-downstream node-upstream node to distribute the output indicators of inter-cluster coordination within the cluster; In addition, in view of the situation that the cluster cannot receive the output indicators due to communication failure, The intra-cluster autonomy control model is constructed with the goal of minimum voltage deviation and minimum network loss of the dominant node in the cluster. The distributed photovoltaic inter-cluster coordination + intra-cluster autonomy two-layer regulation strategy is used to simulate the improved IEEE33-nodes system under multiple scenarios. The results show that the proposed control strategy can effectively solve the voltage overlimit, power flow back and other problems, and play an important role in ensuring the safe and economic operation of the system.

Supply Chain Transparency and Blockchain Design

Companies that are investing in blockchain technology to enhance supply chain transparency face challenges in fostering collaborations with others and deciding what information to share. Transparency over the actions of supply chain partners can improve operational decisions, but sharing own data on the blockchain can put firms at a competitive disadvantage. In this paper, we investigate the resulting questions of when blockchain should be adopted in a supply chain and how it should be designed by analyzing two ways that it can enhance supply chain transparency: making the manufacturer’s sourcing cost transparent to the buyers (i.e., vertical cost transparency) and making the ordering status of buyers transparent to each other (i.e., horizontal order transparency). Given such transparency, firms can design a smart contract that automates transactions contingent on the revealed information and enables them to realize better equilibrium outcomes. We find that blockchain increases supply chain profit only when the manufacturer’s capacity is large and decreases supply chain profit otherwise. If the capacity is sufficiently large to eliminate the buyers’ competition, blockchain leads to a win–win–win and the incentives of all participants are naturally aligned. If the capacity is only moderately large, the manufacturer needs to compensate the buyers to facilitate a blockchain implementation. However, if the capacity is small, horizontal order transparency enabled by the blockchain mitigates the buyers’ overorder incentive to compete for the manufacturer’s capacity and increases double marginalization. For such cases, we show that a blockchain that only enables vertical cost transparency should (and can) still be adopted in a range of small capacity cases, and we propose an access control layer for the logistics data to implement such a blockchain. This paper was accepted by David Simchi-Levi, operations management. Funding: J. Liu was supported by the National Natural Science Foundation of China [Grant 72101110] and The MOE (Ministry of Education in China) Project of Humanities and Social Sciences [Grant 20YJC630084]. Supplemental Material: The online appendix is available at https://doi.org/10.1287/mnsc.2023.4851 .

Hierarchical bi-level load frequency control for multi-area interconnected power systems

To overcome the shortcomings of proportional–integral (PI) control, a linear quadratic regulator (LQR) is proposed in this study, to determine the set points of the PI controllers in a two-level hierarchical manner. The application of the proposed scheme is studied on load frequency control (LFC) of a power system with multiple control areas (CAs). At the lower control level, a discrete PI controllers are used to regulate the frequency and tie-line powers of each of the CAs. To achieve an improved closed loop performance, the local PI controllers are optimally tuned using moth flame optimization (MFO) algorithm by minimizing the Integral Square Error (ISE) of the state errors with respect to local information and interactions with neighboring CAs. While at the upper control layer, an optimized finite-horizon LQR is applied as a guide to establish the optimal set-points of the lower level PI controllers. Since only few of the state variables can be accessed, Kalman filter (KF) is applied as an observer for the estimation of the remaining states. The efficacy of the proposed scheme is verified by implementing it on a three-CA system perturbed with a step and random net disturbances formed by combining the fluctuations in the output power of DFIG-based wind turbine generator and random load demand. From the simulation results, it is established that the proposed LQR-PI supervisory scheme has outperformed the conventional PI control scheme in optimality and stability.

A Novel Two-Stage, Dual-Layer Distributed Optimization Operational Approach for Microgrids with Electric Vehicles

As the ownership of electric vehicles (EVs) continues to rise, EVs are becoming an integral part of urban microgrids. Incorporating the charging and discharging processes of EVs into the microgrid’s optimization scheduling process can serve to load leveling, reducing the reliance of the microgrid on external power networks. This paper proposes a novel two-stage, dual-layer distributed optimization operational approach for microgrids with EVs. The lower layer is a distributed control layer, which ensures, through consensus control methods, that every EV maintains a consistent charging/discharging and state of charge (SOC). The upper layer is the optimization scheduling layer, determining the optimal operational strategy of the microgrid using the multiagent reinforcement learning method and providing control reference signals for the lower layer. Additionally, this paper categorizes the charging process of EVs into two stages based on their SOC: the constrained scheduling stage and the free scheduling stage. By employing distinct control methods during these two stages, we ensure that EVs can participate in the microgrid scheduling while fully respecting the charging interests of the EV owners.

Distributed Coordination of Networked Manipulators: A Two-Layer Control Scheme

This article studies the coordination control problem of networked manipulators, where manipulators are actuated to cooperatively transport an unknown object along a prescribed trajectory. It is assumed that the accurate position and velocity information of the trajectory is known only to a subset of manipulators. A two-layer control scheme consisting of an estimation layer and a control layer is developed. At the estimation layer, prescribed-time distributed estimators are designed to estimate the position and velocity of the trajectory. The estimation errors are shown to converge to zero in pre-specified time. At the control layer, an event-driven distributed controller with a dynamic triggering mechanism is proposed, where nonuniform time-varying communication delays are considered. A distinctive feature of the proposed controller is that both control updates and communication occur at certain event instants, and thus control update burden and communication costs are reduced. Moreover, two adaptive time-varying control gains are designed so that the controller can be implemented without requiring any inequality condition or global information. Finally, a simulation platform based on MATLAB Robotics Toolbox is designed and implemented to verify the effectiveness and superiority of the proposed two-layer control scheme.

Layered energy-saving speed planning and control method for electric vehicle on continuous signal lights road

Emergency start-stop in front of signal lights is one of the main reasons for additional energy consumption and ride discomfort of Electric Vehicle (EV). Existing research on this issue rarely takes into account both energy consumption and ride comfort. Therefore, the layered energy-saving speed planning and control method is proposed. The upper is the layer of energy-saving speed planning. This layer reduces energy consumption of EV by reducing the number of stops on continuous signal lights road and minimizing the range of speed change. On this basis, the sinusoidal variable speed curve is used to smooth the acceleration process to improve ride comfort. Finally, the energy-saving speed considering ride comfort is obtained. This layer makes up for the issue that existing research rarely takes into account both energy consumption and ride comfort of EV, and is an extension and innovation of existing research. The lower is the layer of Model Predictive Controller (MPC)-based speed control. Based on the longitudinal dynamics model of EV, the MPC-based speed controller is established to control EV to track the energy-saving speed. The controller is easy to understand and implement, and it is also suitable for other research on EV, which has certain application value. The simulation results show that under various working conditions, the maximum energy consumption of EV passing through continuous signal lights road without stopping is 604.29 kJ/km, and the minimum is 244.76 kJ/km. The energy consumption is lower than that of actual road test, and it can be saved by 23.18 % compared with the method in the same field. The maximum Root Mean Square of accelerations (RMSa) is 0.25 m/s2, and the minimum is 0.10 m/s2. The values of RMSa above are lower than 0.315 m/s2, which indicates that the ride comfort is good. The utilized method can reduce energy consumption of EV, improve its range and ride comfort, which has important reference significance for promoting the development of EV.

Performance Enhancement of Cross-Layer Cognitive Media Access Control Protocol for Wireless Sensing Networks Using Hybrid Intelligent Optimization Approach

In recent times, wireless sensing networks (WSNs) application usage is increased in a great way. Access to the communication channel is handled by the Medium Access Control (MAC) layer. At the MAC, a control channel is utilized to determine collision-free data transport pathways. As a result, with cognitive radio (CR) technology, the control channel architecture is critical to obtaining mandatory quality of Service (QoS). However, latency, network communication delay, and energy consumption are the main problem. In this article, a novel African Buffalo allied Jellfish Optimization (AFJO) is proposed for clustering and optimal Cluster Head (CH) selection. The hybrid intelligence method uses a unique probabilistic assessment rule purpose as a fitness role to find the best data transmission path while avoiding congestion, which is named as Fuzzy Interfaced Red Deer (FIRD). The proposed protocol’s performance is evaluated using Network Simulator (NS2), which takes into account parameters such as energy consumption, computational complexity, and Quality of Service (QoS) performance with radio frequency integrated parameters. The suggested technique decreases energy consumption, end-to-end latency, communication overhead, and maximizes network throughput when compared to state-of-the-art cross layer cognitive mac protocol for WSNs system approaches.

Performance Evaluation CSMA/CA in MAC Layer and Markov Gaussian Memory Impulse Noise Channels in PHY Layer

There is memory impulse noise in urban outdoor/indoor mobile channels, underwater acoustic channels, powerline communications (PLC) channels, etc. The prior works about network performance evaluation in impulse noise channels considered both the impulse noise in the physical (PHY) layer and CSMA/CA in the media access control (MAC) layer but they used simpler memoryless impulse noise model. In this paper, we propose to use 3-D Markov chain and power iteration method to analyze the throughput of CSMA/CA protocols with finite queue and more general memory impulse noise. The numerical results show that when the impulse noise is strong (impulse noise to Gaussian noise ratio R=150), the normalized throughput would be significantly lower than the case without impulse noise (R=0). Therefore, throughput analysis considering the impulse noise effect is essential.

Gellan Gum and Polyvinyl Alcohol Based Triple-Layer Films Enriched with Alhagi sparsifolia Flower Extract: Preparation, Characterization, and Application of Dried Shrimp Preservation.

To meet the demand for biobased packaging and minimize the oxidation of dried aquatic goods during storage, we created a triple-layer film (TF) with antioxidant capacity. The film was produced using polyvinyl alcohol (PVA) as the protective layer, gellan gum (GG)/PVA composite incorporating Alhagi sparsifolia flower extract (AFE) as the anti-oxidative capability layer, and GG as the anti-oxidative capacity slow-release control layer. The TFs with different AFE additions were characterized and compared to a single-layer film (SF) made of the same material. The results demonstrate that adding AFE to films degraded their water vapour and oxygen barrier properties as well as their tensile strength, but increased their light barrier properties, elongation at break, and anti-oxidative capability. The three-layer structure increased the light, water vapour, and oxygen barrier qualities of films, as well as their slow-release anti-oxidative capability. The application experiment revealed that the inclusion of AFE might aid in the preservation of dried prawn quality. Using TF supplemented with 5 (w/v) AFE to package the dried shrimps reduced the TBARS value by 47.5%. Our research indicated that TFs containing AFE have a wide range of possible applications in dried shrimp preservation.

A three-layer hierarchical model-based approach for network-wide traffic signal control

This paper introduces a three-layer hierarchical model-based approach for network-wide traffic signal control, which consists of a region coordination layer, an intersection coordination layer and a local signal control layer. The hierarchical control problem is formulated by two model predictive control (MPC) schemes. The upper-level control deals with the region coordination problem, which considers the cycle length optimization for different regions based on the macroscopic fundamental diagram. Under the guidance of the upper level MPC, a distributed MPC is developed to address both the green split optimization at each local intersection and the intersection coordination. For computational efficiency, the network is decomposed into separated intersections while the Lagrangian algorithm is developed for intersection coordination. Experimental results on the Nguyen-Dupuis network prove that our proposed three-layer hierarchical control approach has great potential in reducing the computational complexity while maintaining the overall performance (such as total travel time) of the traffic network.

금융권의 제로 트러스트 보안모델 적용방안에 관한 연구

The changed hybrid work environment such as the expansion of cloud computing technology and the increase in telecommuting due to the coronavirus infection (COVID-19), has brought about new security problems. The traditional perimeter security model has limitations in protecting various devices and environments because it is difficult to clearly distinguish network boundaries. The Zero Trust model, which has been proposed as an alternative security strategy to overcome this, is based on the premise that there is no trust in the assets and actors that are connected components when configuring corporate infrastructure and workflow. The financial sector is actively seeking to introduce the zero trust security model as a means of strengthening security. Demand for responding to advanced cyber-security threats, strengthening security policies, and applicability and necessity of a zero trust security model in the financial sector has expanded. This study proposed the components of a zero trust security model to be applied to the financial world based on financial governance and zero trust principles, components of the maturity model, and the results of expert interviews. The zero trust security model in the financial sector consists of four layers and eight detailed steps: perimeter security layer, authority definition layer, behavior detection layer, and internal control layer. This zero trust security model for the financial sector is expected to provide guidelines for key elements and construction steps to be considered when introducing zero trust in the financial sector.

A hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data

Traffic bottlenecks significantly influence the operation efficiency of large-scale road networks. Developing advanced control strategies for bottleneck optimization is a cost-efficient and critical way to deal with network congestion. However, the state-of-the-art studies on network congestion control focus on the topology level, which may fail to relieve congestion by addressing the root cause of bottleneck. This study proposed a hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data. First, the bottleneck-related sub-network (BRS) was identified by tracing vehicle trajectories upstream and downstream of the bottleneck based on the traffic flow propagation. Then, a hierarchical control framework was proposed for BRS optimization. Specifically, in the outer layer, i.e., the gating control layer, the multigated intersections in BRS were controlled via a multimemory deep Q-network approach to optimize the network traffic distribution. In the inner layer, i.e., the coordinated control layer, local intersection controllers were coordinated by adjusting the dynamic input and output streams of the bottleneck under the guidance of the outer layer controller, which helps balance the traffic pressure within BRS and avoids congestion transferring in the network. Both simulation and field experiments were conducted to verify the performance of the proposed hierarchical framework. Results reveal that the framework can effectively relieve network traffic congestion with decreased queue length and travel time.

Camel skin-fat structure inspired MXene@PVA/PCC aerogel composite for efficient medium and low temperature infrared stealth

Infrared stealth materials are in increasing demand with the development of infrared detection technology. However, most reported materials focus solely on emissivity control or temperature control, resulting in brief and less ideal infrared stealth effect. Herein, a double layer MXene@polyvinyl alcohol (PVA)/phase change capsules (PCC) aerogel composite inspired by the skin-fat structure of camel for infrared camouflage was successfully fabricated via a facile freeze-drying followed by spraying method. The PVA/PCC aerogel composite with high latent heat (155.2 J/g) and strong mechanical properties (772.6 kPa), obtained by an in-situ one-step method, is adopted as a temperature control layer, benefiting from the prominent thermal insulation of porous structure and effective heat absorption of PCC. The low emissivity (0.249) of the MXene layer on the surface of aerogel composite makes its radiation temperature recognized by the thermal imager much lower than its actual temperature. By integrating thermal insulation, heat absorption and emissivity reduction strategies, MXene@PVA/PCC aerogel shows no difference with the background in the infrared thermal imager (radiation temperature difference less than 10 °C), achieving superior infrared stealth for medium and low temperature scenarios, and provides novel ideas for developing more high-performance infrared stealth materials.

Heart disease severity level identification system on Hyperledger consortium network.

Electronic Health Records (EHRs) play a vital role in the healthcare domain for the patient survival system. They can include detailed information such as medical histories, medications, allergies, immunizations, vital signs, and more. It can help to reduce medical errors, improve patient safety, and increase efficiency in healthcare delivery. EHR approaches are proven to be an efficient and successful way of sharing patients' personal health information. These kinds of highly sensitive information are vulnerable to privacy and security associated threats. As a result, new solutions must develop to meet the privacy and security concerns in health information systems. Blockchain technology has the potential to revolutionize the way electronic health records (EHRs) are stored, accessed, and utilized by healthcare providers. By utilizing a distributed ledger, blockchain technology can help ensure that data is immutable and secure from tampering. In this article, a Hyperledger consortium network has been developed for sharing health records with enhanced privacy and security. The attribute based access control (ABAC) mechanism is used for controlling access to electronic health records. The use of ABAC on the network provides EHRs with an extra layer of security and control, ensuring that only authorized users have access to sensitive data. By using attributes such as user identity, role, and health condition, it is possible to precisely control access to records on blockchain. Besides, a Gaussian naïve Bayes algorithm has been integrated with this consortium network for prediction of cardiovascular disease. The prediction of cardiovascular is difficult due to its correlated risk factors. This system is beneficial for both patients and physicians as it allows physicians to quickly identify high-risk patients and easily provide them with patient severity level using feature weight prediction algorithms. Dynamic emergency access control privileges are used for the emergency team and will be withdrawn once the emergency has been resolved, depending on the severity score. The system is implemented with the following medical datasets: the heart disease dataset, the Pima Indian diabetes dataset, the stroke prediction dataset, and the body fat prediction dataset. The above datasets are obtained from the Kaggle repository. This system evaluates system performance by simulating various operations using the Hyperledger Caliper benchmarking tool. The performance metrics such as latency, transaction rate, resource utilization, etc. are measured and compared with the benchmark.

Cooperative optimization techniques in distributed MAC protocols – a survey

Purpose Cross-layer approach in media access control (MAC) layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in wireless sensor network (WSN) and Internet of Things (IoT) applications. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Game theory optimization for distributed may increase the network performance. The purpose of this study is to survey the various operations that can be carried out using distributive and adaptive MAC protocol. Hill climbing distributed MAC does not need a central coordination system and location-based transmission with neighbor awareness reduces transmission power. Design/methodology/approach Distributed MAC in wireless networks is used to address the challenges like network lifetime, reduced energy consumption and for improving delay performance. In this paper, a survey is made on various cooperative communications in MAC protocols, optimization techniques used to improve MAC performance in various applications and mathematical approaches involved in game theory optimization for MAC protocol. Findings Spatial reuse of channel improved by 3%–29%, and multichannel improves throughput by 8% using distributed MAC protocol. Nash equilibrium is found to perform well, which focuses on energy utility in the network by individual players. Fuzzy logic improves channel selection by 17% and secondary users’ involvement by 8%. Cross-layer approach in MAC layer will address interference and jamming problems. Hybrid distributed MAC can be used for simultaneous voice, data transmissions in WSN and IoT applications. Cross-layer and cooperative communication give energy savings of 27% and reduces hop distance by 4.7%. Choosing the correct objective function in Nash equilibrium for game theory will address fairness index and resource allocation to the nodes. Research limitations/implications Other optimization techniques can be applied for WSN to analyze the performance. Practical implications Game theory optimization for distributed may increase the network performance. Optimal cuckoo search improves throughput by 90% and reduces delay by 91%. Stochastic approaches detect 80% attacks even in 90% malicious nodes. Social implications Channel allocations in centralized or static manner must be based on traffic demands whether dynamic traffic or fluctuated traffic. Usage of multimedia devices also increased which in turn increased the demand for high throughput. Cochannel interference keep on changing or mitigations occur which can be handled by proper resource allocations. Network survival is by efficient usage of valid patis in the network by avoiding transmission failures and time slots’ effective usage. Originality/value Literature survey is carried out to find the methods which give better performance.

Distributed feedback optimisation based optimal power flow control in fully inverter based islanded AC microgrids

AbstractA novel distributed feedback optimisation (FO) based control method is proposed to control grid‐forming inverters (GFMIs) in fully inverter‐based islanded AC microgrids (MGs). The proposed controller has two control layers. The upper layer uses FO to calculate the frequency and voltage setpoints of GFMIs, whereas the lower layer makes GFMIs track these setpoints. The proposed control method takes advantage of the flexibility of voltage control to regulate the system frequency, maintain both active power and reactive power sharing accuracies, keep bus voltage within allowable range and meanwhile preserves the optimality of the closed‐loop system in term of optimal power flow. The gradient descent method is used to solve the proposed FO problem based on the real‐time measurements in the MGs, which is implemented in a distributed way, and thus eliminates the need for a central controller. Case studies show the effectiveness of the proposed method.The cover image is based on the Research Article Distributed feedback optimisation based optimal power flow control in fully inverter based islanded AC microgrids by Y. Cheng et al., https://doi.org/10.1049/stg2.12132.

Cross-Layer Optimization on Different Data Rates for Efficient Performance in Wireless Sensor Network

The traditional protocols used in wireless sensor networks adhere to stringent layering approaches, which decreases the performance of the quality of service (Quality of Service) metrics. As per specifications 802.15.4, wireless sensor networks are inexpensive and energy efficient. It is essential for evaluating the performance of WSNs. Researchers have looked into the fundamental aspects of a single physical layer and the medium access control (MAC) layer protocol using methodologies calculated using several mathematical models or experimental approaches, respectively. In this research, we offer an improved cross-layer analytical model that utilises a thorough combining and interacting of a Markov chain model of the MAC layer's propagation with a model of the PHY layer's propagation. This combination and interaction are described in detail. Various Quality of Service (quality of service) statistics are presented and evaluated, and a cross-layer effectiveness degradation study is conducted under different inputs of multi-parameter vectors. Other parameters, such as Average Wait Time, Reliability, Failure Probability, and Throughput, have been estimated from the simulation results and contrasted with standardised models. The cross-layer model provides a more thorough performance study with various cross-layer parameter sets, some of which comprise distance, power transmission, and offered loads, among other things.

Key Technologies for a Beyond-100G Next-Generation Passive Optical Network

The explosive development of emerging telecommunication services has stimulated a huge growth in bandwidth demand as people seek universal access to telecommunication networks. In addition, the kinds of services of an existing optical access network are becoming more flexible. In order to provide higher capacity and meet higher transmission performance requirements, it is necessary to further explore the application of the beyond-100G passive optical network (PON). This paper offers a comprehensive review and outline of the prospects of technologies for bringing a beyond-100G PON to practical applications in the future. We review the current existing technologies, mainly in terms of the physical layer and higher media access control layer. These key technologies for the beyond-100G PON, which plays an increasingly significant role, include the advanced multiplexing technology, physical layer digital signal processing technology, infrastructure-sharing technology, security protection technology, and intelligent control management key technologies. Finally, open issues and new challenges for the next-generation PON are focused upon.