Ultimately Bounded Output Feedback Control for Networked Nonlinear Systems With Unreliable Communication Channel: A Buffer-Aided Strategy

This paper concerns ultimately bounded output-feedback control problems for networked systems with unknown nonlinear dynamics. Sensor-to-observer signal transmission is facilitated over networks that has communication constraints.These transmissions are carried out over an unreliable communication channel. In order to enhance the utilization rate of measurement data, a buffer-aided strategy is novelly employed to store historical measurements when communication networks are inaccessible. Using the neural network technique, a novel observer-based controller is introduced to address effects of signal transmission behaviors and unknown nonlinear dynamics.Through the application of stochastic analysis and Lyapunov stability, a joint framework is constructed for analyzing resultant system performance under the introduced controller. Subsequently, existence conditions for the desired output-feedback controller are delineated. The required parameters for the observerbased controller are then determined by resolving some specific matrix inequalities. Finally, a simulation example is showcased to confirm method efficacy.

Quantum Communication Networks and Trust Management: A Survey

This paper summarizes the state of art in quantum communication networks and trust management in recent years.As in the classical networks,trust management is the premise and foundation of quantum secure communication and cannot simply be attributed to security issues,therefore the basic and importance of trust management in quantum communication networks should be taken more seriously.Compared with other theories and techniques in quantum communication,the trust of quantum communication and trust management model in quantum communication network environment is still in its initial stage.In this paper,the core technologies of establishing secure and reliable quantum communication networks are categorized and summarized,and the trends of each direction in trust management of quantum communication network are discussed in depth.

H-infinity performance optimization for networked control systems with limited communication channels

This paper studies the problems of H-infinity performance optimization and controller design for continuous-time NCSs with both sensor-to-controller and controller-to-actuator communication constraints （limited communication channels）. By taking the derivative character of network-induced delay into full consideration and defining new Lyapunov functions, linear matrix inequalities （LMIs）-based H-infinity performance optimization and controller design are presented for NCSs with limited communication channels. If there do not exist any constraints on the communication channels, the proposed design methods are also applicable. The merit of the proposed methods lies in their Jess conservativeness, which is achieved by avoiding the utilization of bounding inequalities for cross products of vectors. The simulation results illustrate the merit and effectiveness of the proposed H-infinity controller design for NCSs with limited communication channels.

STUDY ON THE OPTIMIZATION OF TRANSPORT CONTROL POLICY IN COMMUNICATION NETWORK

In communication networks with policy-based Transport Control on-Demand (TCoD) function,the transport control policies play a great impact on the network effectiveness. To evaluate and optimize the transport policies in communication network,a policy-based TCoD network model is given and a comprehensive evaluation index system of the network effectiveness is put forward from both network application and handling mechanism perspectives. A TCoD network prototype system based on Asynchronous Transfer Mode/Multi-Protocol Label Switching (ATM/MPLS) is introduced and some experiments are performed on it. The prototype system is evaluated and analyzed with the comprehensive evaluation index system. The results show that the index system can be used to judge whether the communication network can meet the application requirements or not,and can provide references for the optimization of the transport policies so as to improve the communication network effectiveness.

A Game-Theoretic Perspective on Resource Management for Large-Scale UAV Communication Networks

As a result of rapid development in electronics and communication technology,large-scale unmanned aerial vehicles(UAVs)are harnessed for various promising applications in a coordinated manner.Although it poses numerous advantages,resource management among various domains in large-scale UAV communication networks is the key challenge to be solved urgently.Specifically,due to the inherent requirements and future development trend,distributed resource management is suitable.In this article,we investigate the resource management problem for large-scale UAV communication networks from game-theoretic perspective which are exactly coincident with the distributed and autonomous manner.By exploring the inherent features,the distinctive challenges are discussed.Then,we explore several gametheoretic models that not only combat the challenges but also have broad application prospects.We provide the basics of each game-theoretic model and discuss the potential applications for resource management in large-scale UAV communication networks.Specifically,mean-field game,graphical game,Stackelberg game,coalition game and potential game are included.After that,we propose two innovative case studies to highlight the feasibility of such novel game-theoretic models.Finally,we give some future research directions to shed light on future opportunities and applications.

Neural-Network-Based Control for Discrete-Time Nonlinear Systems with Input Saturation Under Stochastic Communication Protocol

In this paper,an adaptive dynamic programming(ADP)strategy is investigated for discrete-time nonlinear systems with unknown nonlinear dynamics subject to input saturation.To save the communication resources between the controller and the actuators,stochastic communication protocols(SCPs)are adopted to schedule the control signal,and therefore the closed-loop system is essentially a protocol-induced switching system.A neural network(NN)-based identifier with a robust term is exploited for approximating the unknown nonlinear system,and a set of switch-based updating rules with an additional tunable parameter of NN weights are developed with the help of the gradient descent.By virtue of a novel Lyapunov function,a sufficient condition is proposed to achieve the stability of both system identification errors and the update dynamics of NN weights.Then,a value iterative ADP algorithm in an offline way is proposed to solve the optimal control of protocol-induced switching systems with saturation constraints,and the convergence is profoundly discussed in light of mathematical induction.Furthermore,an actor-critic NN scheme is developed to approximate the control law and the proposed performance index function in the framework of ADP,and the stability of the closed-loop system is analyzed in view of the Lyapunov theory.Finally,the numerical simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

A FUZZY-LOGIC CONTROL ALGORITHM FOR ACTIVE QUEUE MANAGEMENT IN IP NETWORKS

Active Queue Management (AQM) is an active research area in the Internet community. Random Early Detection (RED) is a typical AQM algorithm, but it is known that it is difficult to configure its parameters and its average queue length is closely related to the load level. This paper proposes an effective fuzzy congestion control algorithm based on fuzzy logic which uses the pre- dominance of fuzzy logic to deal with uncertain events. The main advantage of this new congestion control algorithm is that it discards the packet dropping mechanism of RED, and calculates packet loss according to a preconfigured fuzzy logic by using the queue length and the buffer usage ratio. Theo- retical analysis and Network Simulator (NS) simulation results show that the proposed algorithm achieves more throughput and more stable queue length than traditional schemes. It really improves a router's ability in network congestion control in IP network.

Robust control for a class of nonlinear networked systems with stochastic communication delays via sliding mode conception

This paper deals with the robust control problem for a class of uncertain nonlinear networked systems with stochastic communication delays via sliding mode conception （SMC）. A sequence of variables obeying Bernoulli distribution are employed to model the randomly occurring communication delays which could be different for different state variables. A discrete switching function that is different from those in the existing literature is first proposed. Then, expressed as the feasibility of a linear matrix inequality （LMI） with an equality constraint, sufficient conditions are derived in order to ensure the globally mean-square asymptotic stability of the system dynamics on the sliding surface. A discrete-time SMC controller is then synthesized to guarantee the discrete-time sliding mode reaching condition with the specified sliding surface. Finally, a simulation example is given to show the effectiveness of the proposed method.

A Controller-Based Architecture for Information Centric Network Construction and Topology management

Information-Centric Networking(ICN) has recently emerged as a result of the increased demand to access contents regardless of their location in the network services. This new approach facilitates content distribution as a service of the network with lower delay and higher security in comparison with the current IP network. Applying ICN in current IP infrastructure leads to major complexities. One approach to deploy ICN with less complexity is to integrate ICN with Software Defined Networking(SDN). The SDN controller manages the content distribution, caching, and routing based on the users' requests. In this paper, we extend these context by addressing the ICN topology management problem over the SDN network to achieve an improved user experience as well as network performance. In particular, a centralized controller is designed to construct and manage the ICN overlay. Experimental results indicate that this adopted topology management strategy achieves high performance, in terms of low failure in interest satisfaction and reduced download time compared to a plain ICN.

Interference management via access control and mobility prediction in two-tier heterogeneous networks

Abstract： Two-tier heterogeneous networks （HetNets）, where the current cellular networks, i.e., macrocells, are overlapped with a large number of randomly distributed femtocells, can potentially bring significant benefits to spectral utilization and system capacity. The interference management and access control for open and closed femtocells in two-tier HetNets were focused. The contributions consist of two parts. Firstly, in order to reduce the uplink interference caused by MUEs （macrocell user equipments） at closed femtocells, an incentive mechanism to implement interference mitigation was proposed. It encourages femtoeells that work with closed-subscriber-group （CSG） to allow the interfering MUEs access in but only via uplink, which can reduce the interference significantly and also benefit the marco-tier. The interference issue was then studied in open-subscriber-group （OSG） femtocells from the perspective of handover and mobility prediction. Inbound handover provides an alternative solution for open femtocells when interference turns up, while this accompanies with PCI （physical cell identity） confusion during inbound handover. To reduce the PCI confusion, a dynamic PCI allocation scheme was proposed, by which the high handin femtocells have the dedicated PCI while the others share the reuse PCIs. A Markov chain based mobility prediction algorithm was designed to decide whether the femtoeell status is with high handover requests. Numerical analysis reveals that the UL interference is managed well for the CSG femtocell and the PCI confusion issue is mitigated greatly in OSG femtocell compared to the conventional approaches.

Admission control based on beamforming and interference alignment for D2D communication underlaying cellular networks

An admission control algorithm based on beamforming and interference alignment for device-to-device( D2D) communication underlaying cellular networks is proposed. First, some portion of D2D pairs that are the farthest away from the base station( BS) is selected to perform joint zero-forcing beamforming together with the cellular user equipments( UEs) and is admitted to the cellular network. The interference of the BS transmitting signal to the cellular UEs and the portion of D2D pair is eliminated completely at the same time. Secondly,based on the idea of interference alignment,the definition of channel parallelism is given. The channel parallelism of the remaining D2D pairs which are not involved in joint zero-forcing beamforming is computed by using the channel state information from the BS to the D2D devices. The higher the channel parallelism,the less interference the D2D pair suffers from the BS. Finally,in a descending order of channel parallelism,the remaining D2D pairs are reviewed in succession to determine admission to the cellular network. The algorithm stops when the admission of a D2D pair decreases the system sum rate. Simulation results show that the proposed algorithm can effectively reduce the interference of the BS transmitting signal for D2D pairs and significantly improve system capacity. Furthermore, D2D communication is more applicable to short-range links.

Risk Management of Clinical Reference Dosimetry of a Large Hospital Network Using Statistical Process Control

Managing TG-51 reference dosimetry in a large hospital network can be a challenging task. The objectives of this study are to investigate the effectiveness of using Statistical Process Control (SPC) to manage TG-51 workflow in such a network. All the sites in the network performed the annual reference dosimetry in water according to TG-51. These data were used to cross-calibrate the same ion chambers in plastic phantoms for monthly QA output measurements. An energy-specific dimensionless beam quality cross-calibration factor, , was derived to monitor the process across multiple sites. The SPC analysis was then performed to obtain the mean, , standard deviation, σk, the Upper Control Limit (UCL) and Lower Control Limit (LCL) in each beam. This process was first applied to 15 years of historical data at the main campus to assess the effectiveness of the process. A two-year prospective study including all 30 linear accelerators spread over the main campus and seven satellites in the network followed. The ranges of the control limits (±3σ) were found to be in the range of 1.7% - 2.6% and 3.3% - 4.2% for the main campus and the satellite sites respectively. The wider range in the satellite sites was attributed to variations in the workflow. Standardization of workflow was also found to be effective in narrowing the control limits. The SPC is effective in identifying variations in the workflow and was shown to be an effective tool in managing large network reference dosimetry.

Design of Power Communication Data Network Management System and Implementation of Data Acquisition Module

The power communication network is a separate network from the power grid whose primary purpose is to ensure the power grid's safe operation.This paper expounds the composition of the comprehensive network management architecture of the power communication data network and the implementation of the data acquisition module in the network management system through theoretical analysis,for the reference of relevant personnel,in order to better promote the collection of power grid communication network data.

Model-based predictive controller design for a class of nonlinear networked systems with communication delays and data loss

This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation re- suits demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.

Management and Control of Outsourcing in Dispersed Network Manufacturing Systems

The trend of economic globalisation and advances in i nformation technology has led to the emergence of dispersed manufacturing system s as a form of the virtual organisation. New manufacturing strategy pays more at tention to the management of the total value chain and therefore puts emphasis o n outsourcing. In fact, outsourcing is an efficient way of utilizing available r esources and has become one key aspect of the manufacturing strategy. Improved d ecision and organization on outsourcing will result in cost production and short er lead-times. However, most concepts and practice of traditional outsourcing do not adapt to t he changing environment and meet increasing performance requirements. On the oth er hand, virtual organisations might display instability between pure outsourcin g and establishing alliance. Balance and trade-off between independent agents a nd creating alliance are thus required. Therefore, the purpose of this paper is to develop a model to support decision-making, management and control on outsou rcing in a dispersed network manufacturing system and to discuss several key iss ues that are relevant to the relationship between the agents of the network. Dev elopment of the model will deploy Applied System Theory and will be built on fou ndations of earlier research on industrial management such the theories of Outso urcing, Order Entry Points, Design of Organisations and Logistic Control. The is sues that will be addressed in this paper are: · The selection of suppliers and co-makers; · Communication between suppliers and clients; · The mechanisms for profit-sharing between agents; · The product data management to integrate the knowledge of the different agent s into product design. Industrial companies will benefit from this research by the practical methods an d implementation extending their business models beyond concepts for outsourcing and alliances. Additionally, the exploration will lead to proactive contributio n of manufacturing during engineering, which would improve management and contro l of dispersed manufacturing systems.

The Sharing Management of Digital Communication Network Resource

Along with the mature development of the domestic computer technology and communication technology, it is an inevitable trend to integrate the two major information technologies together in the future reform of the social communication model. Under this background, the principle of digital communication is introduced first in this paper, and accordingly the role of the communication network resources sharing is analyzed, and finally the sharing management of digital communication network resources is proposed. Hopefully. this paper can play a help in the future subsequent study.

The Sharing Management of Digital Communication Network Resource

Along with the mature development of the domestic computer technology and communication technology, it is an inevitable trend to integrate the two major information teclmologies together in the future reform of the social communication model. Under this background, the principle of digital co,nmunication is introduced first in this paper, and accordingly the role of the communication network resources sharing is analyzed, and finally the sharing management of digital communication network resources is proposed. Hopefully, this paper can play a help in the future subsequent study.

Neural-network-based fully distributed formation control for nonlinear multi-agent systems with event-triggered communication

This paper investigates the consensus-based formation control problem for multi-agent systems with unknown nonlinear dynamics.To achieve the desired formation,we propose two formation controllers to achieve the desired formation,one based on system states and the other on system outputs.The proposed controllers utilize adaptive gains to avoid global information and neural networks to estimate and compensate for nonlinearities.The proposed event-triggered schemes avoid continuous communication among agents and exclude the Zeno behavior.Stability analysis reveals that formation errors are bounded,and numerical simulations are used to validate the effectiveness of the proposed approaches.

A device information-centered accelerator control network management system

Purpose The control network is a critical infrastructure that supports the stable operation of the accelerator.Each device accessing the control network has different device information,such as IP address,MAC address,connected switches and ports,device location and purpose.Accurately maintaining the mapping relationship between these device information facilitates network management.It helps inventory assets,fault location and provide visibility into dynamic changes of device on the network.However,existing tools cannot fully satisfy these demands.They only map some information and lack details important for accelerator facilities like device location and purpose.Additionally,they only reflect the current status rather than indicating dynamic changes across all devices over time.As intelligent devices proliferate,the scale of the control network is rapidly expanding,posing greater challenges in maintaining mapping relationships.Methods This paper proposes a device information-centered Accelerator Control Network Management System(ACNMS).It establishes a device information management framework and allows network administrators to perceive the dynamic changes of devices on the network.The system adopts a layered architecture.Back-end modules implement the core logic of all functions.The graphical user interface presents data and provides a management portal.Results The system test on the control network of the National Synchrotron Radiation Laboratory demonstrates that it can meet the functional design objectives.The application scenarios of the ACNMS are further expanded through system integration and combination with network automation.Conclusion The ACNMS has proven to be an efficient network management tool that significantly improves the operation and maintenance efficiency of the accelerator control network.

Distributed robust power control in two-tier vehicle networks under uncertain channel environments

This paper proposes a novel optimization scheme to support stable and reliable vehicle-to-everything connections in two-tier networks,where the uplink channel of the cellular user is reused by underlay vehicle-to-vehicle communications.However,considering complex channel fading and high-speed vehicle movement,the cer-tainty assumption is impractical and fails to maintain power control strategy in reality in the traditional statical vehicular networks.Rather than the perfect channel state information assumption,the first-order Gauss-Markov process which is a probabilistic model affected by vehicle speed and fading is introduced to describe imperfect channel gains.Moreover,interference management is a major challenge in reusing communications,especially in uncertain channel environments.Power control is an effective way to realize interference management,and optimal power allocation can ensure that interference of the user meets the communication requirements.In this study,the sum-rate-oriented power control scheme and minimum-rate-oriented power control scheme were implemented to manage interference and satisfy different design objectives.Since both of these schemes are non-convex and intractable,the Bernstein approximation and successive convex approximation methods were adopted to transform the original problems into convex ones.Furthermore,a novel distributed robust power control al-gorithm was developed to determine the optimal solutions.The performance of the algorithm was evaluated through numerical simulations,and the results indicate that the proposed algorithm is effective in vehicular communication networks with uncertain channel environments.