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.

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.

Transmission Technique towards Seamless Handover for NGEO Satellite Networks

This paper presents a seamless transmission technique for Non-Geostationary Earth Orbit(NGEO) satellite networks.The seamless transmission technique combines the concept of Hop-by-Hop and network coding to alleviate the negative impacts of handovers,high bit error rate,and long delay,and to achieve high throughput and complete delivery in NGEO satellite networks.This network coding algorithm is able to maintain expected small queue size and low decoding latency.Furthermore,the seamless transmission technique applies a novel explicit congestion notification mechanism and can achieve high bandwidth utilization.Various aspects of this seamless transmission technique are evaluated.

An Improved Handoff Algorithm for Heterogeneous Wireless Networks

Heterogeneous Wireless Network is currently a major area of focus in communication engineering.But the important issue in recent communication is the approachability to the wireless networks while maintaining the quality of service.Today,all the wireless access networks are working in tandem to keep the users always connected to the internet cloud that matches the price affordability and performance goals.In order to achieve seamless connectivity,due consideration has to be given to handoff precision and a smaller number of handoffs.Several researchers have used heuristic approaches to solve this issue.In the present work,a hybrid intelligent algorithm has been suggested for vertical handoff decisions.This hybrid intelligent algorithm is based on dual optimization approach which uses“Particle Swarm Optimization(PSO)”and“Mobile Robustness Optimization(MRO)”techniques for improving the quality of services.This approach performs well even in the failure network conditions and gives the best results in terms of connectivity.The results at the last has been compared with the conventional techniques and it has been observed that the proposed methodology outperforms the existing one.

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.

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.

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.

Mean square stability of recurrent neural networks with random delay and Markovian switching

To establish easily proved conditions under which the random delayed recurrent neural network with Markovian switching is mean-square stability,the evolution of the delay was modeled by a continuous-time homogeneous Markov process with a finite number of states.By employing Lyapunov-Krasovskii functionals and conducting stochastic analysis,a linear matrix inequality (LMI) approach was developed to derive the criteria for mean-square stability,which can be readily checked by some standard numerical packages such as the Matlab LMI Toolbox.A numerical example was exploited to show the usefulness of the derived LMI-based stability conditions.

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.

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 Network Calculus Approach for the Analysis of Packet-switching Networks

Network calculus is an evolving new methodology for backlog and delay analysis of packet-switching networks. With network calculus we are able to compute tight bounds on delays,backlogs,and effective bandwidths in a lossless setting applicable to packet-switching networks and better understand some physical properties of networks. In this paper,the basic network calculus concepts of arrival curves and service curves are introduced.Then we provide the approach for modeling leaky-bucket,generic cell rate algorithm(GCRA),constant bit rate(CBR)flow, variable bit rate(VBR) flow with arrival curve.It is shown that all rate-based packet schedulers can be by a simple rate latency service curve.And by applying these fundamental rules of network calculus,bounds on delay, buffer,effective bandwidth for leaky bucket,GCRA,CBR and VBR can be derived and some practical examples are given.Finally,we compare all the results obtained and conclude this paper.

Modeling and Real-ti me Performance Analysis of Switched Ethernet by Network Calculus

The real-time performance of switched Ethernet is a hot research field. However, there isn’t any effective modeling to describe it until now. Through analyzing the structure of classical switch, a switch model by network calculus is proposed, in which the data flow is divided into real-time flow and non real-time flow and the arrival curve, service curve, the max delay and max storage needed are got. The max delay provides theory direction for transmitting real-time data in switched Ethernet and the max storage provides the theory reference for constructing switch in real-time industrial Ethernet.

5G Flexible Optical Transport Networks with Large-Capacity, Low-Latency and High-Efficiency

The fifth generation(5G) of mobile communications are facing big challenges, due to the proliferation of diversified terminals and unprecedented services such as internet of things(IoT), high-definition videos, virtual/augmented reality(VR/AR). To accommodate massive connections and astonish mobile traffic, an efficient 5G transport network is required. Optical transport network has been demonstrated to play an important role for carrying 5G radio signals. This paper focuses on the future challenges, recent studies and potential solutions for the 5G flexible optical transport networks with the performances on large-capacity, low-latency and high-efficiency. In addition, we discuss the technology development trends of the 5G transport networks in terms of the optical device, optical transport system, optical switching, and optical networking. Finally, we conclude the paper with the improvement of network intelligence enabled by these technologies to deterministic content delivery over 5G optical transport networks.

Robust Feedback Set Stabilization of Logic Networks with State-Dependent Uncertain Switching and Control Constraints

This study investigates the robust feedback set stabilization of switched logic control networks(SLCNs)with state-dependent uncertain switching and control constraints.First,based on the properties of the semi-tensor product of matrices and the vector representation of logic,an SLCN with state-dependent uncertain switching and control constraints is expressed in algebraic form.Second,an input transformation and a switching model are constructed to transfer the original SLCN into one with a free control input and arbitrary switching.The equivalence between the set stabilizability of the original SLCN and that of the resulting SLCN is established.Based on such equivalence,the authors propose a necessary and sufficient condition for robust feedback set stabilizability.Finally,an example is presented to demonstrate the application of the results obtained.

Accurate 3D Thermal Network Development for Direct-drive Outer-rotor Hybrid-PM Flux-switching Generator

Heat and thermal problems are major obstacles to achieving high power density in compact permanent magnet(PM)topologies.Consequently,a comprehensive,accurate,and rapid temperature rise estimation method is required for novel electric machines to ensure safe and reliable operations.A unique three-dimensional(3D)lumped parameter thermal network(LPTN)is presented for accurate thermal modeling of a newly developed outer-rotor hybrid-PM flux switching generator(OR-HPMFSG)for direct-drive applications.First,the losses of the OR-HPMFSG are calculated using 3D finite element analysis(FEA).Subsequently,all machine components considering the thermal contact resistance,anisotropic thermal conductivity of materials,and various heat flow paths are comprehensively modeled based on the thermal resistances.In the proposed 3-D LPTN,internal nodes are considered to predict the average temperature as well as the hot spots of all active and passive components.Experimental measurements are performed on a prototype OR-HPMFSG to validate the efficiency of the 3-D LPTN.A comparison of the results at various operating points between the developed 3-D LPTN,experimental test,and FEA indicates that the 3-D LPTN quickly approximates the hotspot and mean temperature of all components under both transient and steady states with high accuracy.

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.

Asymptotic stability and disturbance attenuation properties for a class of networked control systems

In this paper, stability and disturbance attenuation issues for a class of Networked Control Systems （NCSs） under uncertain access delay and packet dropout effects are considered. Our aim is to find conditions on the delay and packet dropout rate, under which the system stability and H∞ disturbance attenuation properties are preserved to a desired level. The basic idea in this paper is to formulate such Networked Control System as a discrete-time switched system. Then the NCSs＇ stability and performance problems can be reduced to the corresponding problems for switched systems, which have been studied for decades and for which a number of results are available in the literature. The techniques in this paper are based on recent progress in the discrete-time switched systems and piecewise Lyapunov functions.