Deployment of the Content-Based Switching Network

In this paper, we propose a hybrid network architecture, called Content-based Switching Network (CSN), and its signaling scheme, which addresses the issues inherent to conventional hybrid networks which implement a horizontal separation over the entire network (from edge to edge). We will show how CSN nodes can flexibly choose their switching paradigm (store-and-forward, optical bypass, electrical bypass) during a path establishment. Contents being transferred in one piece from end-to-end, the concept of packet can be eluded in our network, and, in particular, the user is able to avoid complicated transport layer functions, like TCP, if they are not essential. In CSN, very large contents have a special status, since they cannot be store-and-forwarded. We will show how the resource management has been designed in order to deal with such contents. A section is dedicated to deployment and feasibility issues. Simulation results will show that CSN can successfully transfer contents at 1 Gbps and 10 Gbps, the maximum speed being limited by the state-of-the-art device technologies when buffering is required (memory speed), while no major limit is observed in the case of all-optical transfers other than the optical fiber speed. Other results concern the deployment of CSN from an unclean slate approach. They will show how beneficial can be the deployment of CSN from an Optical Circuit Switching network.

Event-triggered H_(∞) PI state estimation for delayed switched neural networks

On state estimation problems of switched neural networks,most existing results with an event-triggered scheme(ETS)not only ignore the estimator information,but also just employ a fixed triggering threshold,and the estimation error cannot be guaranteed to converge to zero.In addition,the state estimator of non-switched neural networks with integral and exponentially convergent terms cannot be used to improve the estimation performance of switched neural networks due to the difficulties caused by the nonsmoothness of the considered Lyapunov function at the switching instants.In this paper,we aim at overcoming such difficulties and filling in the gaps,by proposing a novel adaptive ETS(AETS)to design an event-based H_(∞)switched proportional-integral(PI)state estimator.A triggering-dependent exponential convergence term and an integral term are introduced into the switched PI state estimator.The relationship among the average dwell time,the AETS and the PI state estimator are established by the triggering-dependent exponential convergence term such that estimation error asymptotically converges to zero with H_(∞)performance level.It is shown that the convergence rate of the resultant error system can be adaptively adjusted according to triggering signals.Finally,the validity of the proposed theoretical results is verified through two illustrative examples.

Traffic prediction enabled dynamic access points switching for energy saving in dense networks

To meet the ever-increasing traffic demand and enhance the coverage of cellular networks,network densification is one of the crucial paradigms of 5G and beyond mobile networks,which can improve system capacity by deploying a large number of Access Points(APs)in the service area.However,since the energy consumption of APs generally accounts for a substantial part of the communication system,how to deal with the consequent energy issue is a challenging task for a mobile network with densely deployed APs.In this paper,we propose an intelligent AP switching on/off scheme to reduce the system energy consumption with the prerequisite of guaranteeing the quality of service,where the signaling overhead is also taken into consideration to ensure the stability of the network.First,based on historical traffic data,a long short-term memory method is introduced to predict the future traffic distribution,by which we can roughly determine when the AP switching operation should be triggered;second,we present an efficient three-step AP selection strategy to determine which of the APs would be switched on or off;third,an AP switching scheme with a threshold is proposed to adjust the switching frequency so as to improve the stability of the system.Experiment results indicate that our proposed traffic forecasting method performs well in practical scenarios,where the normalized root mean square error is within 10%.Furthermore,the achieved energy-saving is more than 28% on average with a reasonable outage probability and switching frequency for an area served by 40 APs in a commercial mobile network.

Exponential stabilization of networked control systems and design of switching controller

This paper deals with the problem of switching between an open-loop estimator and a close-loop estimator for compensating transmission error and packet dropout of networked control systems. Switching impulse is considered in order to reduce the error between theory and application, a sufficient condition for exponential stabilization of networked control systems under a given switching rule is presented by multiple Lyapunov-like functions. These results are presented for both continuous-time and discrete-time domains. Controllers are designed by means of linear matrix inequalities. Sim- ulation results show the feasibility and efficiency of the proposed method.

SYNCHRONIZATION OF MASTER-SLAVE MARKOVIAN SWITCHING COMPLEX DYNAMICAL NETWORKS WITH TIME-VARYING DELAYS IN NONLINEAR FUNCTION VIA SLIDING MODE CONTROL

In this article, a synchronization problem for master-slave Markovian switching complex dynamical networks with time-varying delays in nonlinear function via sliding mode control is investigated. On the basis of the appropriate Lyapunov-Krasovskii functional, introducing some free weighting matrices, new synchronization criteria are derived in terms of linear matrix inequalities （LMIs）. Then, an integral sliding surface is designed to guarantee synchronization of master-slave Markovian switching complex dynamical networks, and the suitable controller is synthesized to ensure that the trajectory of the closed-loop error system can be driven onto the prescribed sliding mode surface. By using Dynkin＇s formula, we established the stochastic stablity of master-slave system. Finally, numerical example is provided to demonstrate the effectiveness of the obtained theoretical results.

Resistive Switching Memory of TiO2 Nanowire Networks Grown on Ti Foil by a Single Hydrothermal Method

The resistive switching characteristics of TiO_2 nanowire networks directly grown on Ti foil by a single-step hydrothermal technique are discussed in this paper. The Ti foil serves as the supply of Ti atoms for growth of the TiO_2 nanowires, making the preparation straightforward. It also acts as a bottom electrode for the device. A top Al electrode was fabricated by e-beam evaporation process. The Al/TiO_2 nanowire networks/Ti device fabricated in this way displayed a highly repeatable and electroforming-free bipolar resistive behavior with retention for more than 10~4 s and an OFF/ON ratio of approximately 70. The switching mechanism of this Al/TiO_2 nanowire networks/Ti device is suggested to arise from the migration of oxygen vacancies under applied electric field. This provides a facile way to obtain metal oxide nanowire-based Re RAM device in the future.

Research and Progress of Service Driven Optical Switching Network in China

National R&D activities on optical switching networkare introduced. Optical switching network testbedswere established in China including 3T-net andOBS ring and mesh network test-bed with the supportof national '863' program. As an importantmodule in OPS network, a novel all-optical serialmulticast mode is discussed.

A Study of Optimum Switching Problem for Production Systems Considering Efficiency, Delivery Time and Green Evaluation

This paper aims to derive the optimal switching strategy for production system considering efficiency, delivery time and green evaluation. Nowadays more and more manufacturing and logistics systems not only pursue better work efficiency, but also focus on green energy evaluation issues. Cost reduction and shortening of delivery time are always important management issues in pursuit of efficiency and optimization of the entire production system because of global production competition. In a market situation where customer needs change in various ways, in particular, due to inadequate quality, changes in the local environment, natural disasters and so on. Therefore, prompt planning of management measures such as switching work processes and changing production methods has become an important issue. On the other hand, since the Paris Agreement came into effect, the construction of an environment-friendly production system has been required as an approach to environmental problems such as global warming. In this paper, we propose an optimum switching model of production systems considering efficiency, delivery time and green evaluation using a green evaluation index (GEC: Green Energy Coefficient). We also discuss the optimal switching strategy by numerical observation.

Switching Control Method for Optimal State Feedback Controller of Nuclear Reactor Power System

Due to the nonlinearity of the reactor power system, the load tracking situation is closely related to the initial steady-state power and the final steady-state power after the introduction of the state feedback controller. Therefore, when the initial power and the final stable power are determined, the particle swarm optimization algorithm is used to find the optimal controller parameters to minimize the load tracking error. Since there are many combinations of initial stable power and final stable power, it is not possible to find the optimal controller parameters for all combinations, so the neural network is used to take the final stable power and the initial stable power as input, and the optimal controller parameters as the output. This method obtains the optimal state feedback controller switching control method can achieve a very excellent load tracking effect in the case of continuous power change, in the power change time point, the response is fast, in the controller parameter switching time point, the actual power does not fluctuate due to the change of controller parameters. .

Control method based on DRFNN sliding mode for multifunctional flexible multistate switch

To address the low accuracy and stability when applying classical control theory in distribution networks with distributed generation,a control method involving flexible multistate switches(FMSs)is proposed in this study.This approach is based on an improved double-loop recursive fuzzy neural network(DRFNN)sliding mode,which is intended to stably achieve multiterminal power interaction and adaptive arc suppression for single-phase ground faults.First,an improved DRFNN sliding mode control(SMC)method is proposed to overcome the chattering and transient overshoot inherent in the classical SMC and reduce the reliance on a precise mathematical model of the control system.To improve the robustness of the system,an adaptive parameter-adjustment strategy for the DRFNN is designed,where its dynamic mapping capabilities are leveraged to improve the transient compensation control.Additionally,a quasi-continuous second-order sliding mode controller with a calculus-driven sliding mode surface is developed to improve the current monitoring accuracy and enhance the system stability.The stability of the proposed method and the convergence of the network parameters are verified using the Lyapunov theorem.A simulation model of the three-port FMS with its control system is constructed in MATLAB/Simulink.The simulation result confirms the feasibility and effectiveness of the proposed control strategy based on a comparative analysis.

Discontinuous event-trigger scheme for global stabilization of state-dependent switching neural networks with communication delay

This paper is concerned with the global stabilization of state-dependent switching neural networks(SDSNNs)viadiscontinuous event-triggered control with network-induced communication delay.Aiming at decreasing triggering times,a discontinuous event-trigger scheme is utilized to determine whether the sampling information is required to be sent outor not.Meanwhile,under the effect of communication delay,the trigger condition and SDSNNs are transformed into twotractable models by designing a fictitious delay function.Then,using the Lyapunov–Krasovskii stability theory,someinequality estimation techniques,and extended reciprocally convex combination method,two sufficient criteria are established for ensuring the global stabilization of the resulting closed-loop SDSNNs,respectively.A unified framework isderived that has the ability to handle the simultaneous existence of the communication delay,the properties of discontinuousevent-trigger scheme,as well as feedback controller design.Additionally,the developed results demonstrate a quantitativerelationship among the event trigger parameter,communication delay,and triggering times.Finally,two numerical examples are presented to illustrate the usefulness of the developed stabilization scheme.

H_(∞) state estimation for Markov jump neural networks with transition probabilities subject to the persistent dwell-time switching rule

We investigate the problem of H_(∞) state estimation for discrete-time Markov jump neural networks. The transition probabilities of the Markov chain are assumed to be piecewise time-varying, and the persistent dwell-time switching rule,as a more general switching rule, is adopted to describe this variation characteristic. Afterwards, based on the classical Lyapunov stability theory, a Lyapunov function is established, in which the information about the Markov jump feature of the system mode and the persistent dwell-time switching of the transition probabilities is considered simultaneously.Furthermore, via using the stochastic analysis method and some advanced matrix transformation techniques, some sufficient conditions are obtained such that the estimation error system is mean-square exponentially stable with an H_(∞) performance level, from which the specific form of the estimator can be obtained. Finally, the rationality and effectiveness of the obtained results are verified by a numerical example.

Performance Evaluation of an Internet Protocol Security (IPSec) Based Multiprotocol Label Switching (MPLS) Virtual Private Network

This paper evaluates the performance of Internet Protocol Security (IPSec) based Multiprotocol Label Switching (MPLS) virtual private network (VPN) in a small to medium sized organization. The demand for security in data networks has been increasing owing to the high cyber attacks and potential risks associated with networks spread over distant geographical locations. The MPLS networks ride on the public network backbone that is porous and highly susceptible to attacks and so the need for reliable security mechanisms to be part of the deployment plan. The evaluation criteria concentrated on Voice over Internet Protocol (VoIP) and Video conferencing with keen interest in jitter, end to end delivery and general data flow. This study used both structured questionnaire and observation methods. The structured questionnaire was administered to a group of 70 VPN users in a company. This provided the study with precise responses. The observation method was used in data simulations using OPNET Version 14.5 Simulation software. The results show that the IPSec features increase the size of data packets by approximately 9.98% translating into approximately 90.02% effectiveness. The tests showed that the performance metrics are all well within the recommended standards. The IPSec Based MPLS Virtual private network is more stable and secure than one without IPSec.

Global Synchronization of Directed Networks with Fast Switching Topologies

Global synchronization of a class of directed dynamical networks with switching topologies is investigated.It is found that if there is a directed spanning tree in the fixed time-average of network topology and the time-averageis achieved sufficiently fast,then the network will reach global synchronization for sufficiently large coupling strength.

Cognitive Analysis of Auditory Temporal Sequence Information Difference Based on Network Switching

Auditory sense is an important way for people to receive and interact with foreign information.In different environment,the auditory sense changes.Therefore,it is necessary to find a detection method that can detect hearing in a timely manner.In this paper,EEG experiments were used to construct and compare brain functional networks in different states,and auditory state models were constructed with different auditory input signals.Secondly,the cross-correlation method is used to slice the signal and construct the adjacency matrix.Louvain community detection algorithm is used to process the data and calculate the network conversion rate under different parameters.It is concluded that the network conversion rate can be used to analyze the temporal variation of auditory information under the condition of controlled parameters.This indicates that the network conversion rate can also be used as a method to analyze auditory signals in the future.

An Arrangement of Channels and Transceivers in Optical Packet Switching Networks

Based on a media access and control（MAC）protocol,an arrangement of channels and transceivers in optical packet switching dense wavelength division multiplexing（DWDM）networks is proposed in this paper.In order to reduce the cost of nodes,fixed transmitters and receivers are used instead of tunable transmitters and receivers.Two fixed transmitters and many fixed receivers are used in each node in the scheme.The average waiting delay of this scheme is analyzed through mathematics and computer simulation.The result shows that the property of the scheme is almost the same as using tunable transmitter and receiver.Furthermore,if the tuning time of tunable transmitters is taken into account,the performance of the tunable transmitter scheme is poor than this scheme at the average waiting delay and throughput of the network.

A Novel Switching Architecture for IP Over WDM Networks

Integrating IP and WDM is an attractive direction for research. Many solutions have been presented but it is noted that the existing switching technologies still need more concern. Since optical packet switching is not practical yet, there are just two possible solutions left. One is wavelength routing(WR), which is circuit switching in essence and the other is newly proposed optical burst switching (OBS). In this paper, characteristics of WR and OBS are first described, then, compared in several aspects. It is notice that in many aspects, the wavelength routing and burst switching are complement. This stimulates us to propose a new switching architecture, which may be considered as "mixture" of WR and OBS. We beleve the network built on new switching structure can accommodate the requirements of practicability, flexibility, robustness, effciency and etc. simultaneously. However, many related problems still need to be further researched.

A Service Ratio-Based Dynamic Fair Queueing Algorithm for Packet-Switching Networks

A new weighted fair queueing algorithm is proposed, which uses the novel flow-based service ratio parameters to schedule flows. This solves the main drawback of traditional weighted fair queueing algorithms-the packet-based calculation of the weight parameters. In addition, this paper proposes a novel service ratio calculation method and a queue management technology. The former adjusts the service ratio parameters adaptively based on the dynamics of the packet lengths and then solves the unfairness problem induced by the variable packet length. The latter improves the utilization of the server’s queue buffer and reduces the delay jitter through restricting the buffer length for each flow.