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.

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.

Design of assembly control algorithm based on burst-size feedback for optical burst switching network

A novel assembly control algorithm named burst-size feedback adaptive assembly period （BFAAP） is proposed. The major difference between BFAAP and other similar adaptive assembly algorithms is that the control curve of BFAAP is dynamically adjusted according to the feedback of outgoing burst size. BFAAP is compared with two typical algorithms fixed assembly period （FAP） and min-burst length max- assembly period （MBMAP） in simulation in terms of burst size distribution and assembly period. Moreover, the transmission control protocol （TCP） performance over BFAAP is also considered and simulated.

A new burst assembly technique for supporting QoS in optical burst switching networks

This letter proposes a new burst assembly technique for supporting QoS in optical burst switching (OBS) networks. It consists of the adaptive-threshold burst assembly mechanism and QoS-based random offset-time scheme. The assembly mechanism, which is fit well to multi-class burst assembly, not only matches with IP QoS mechanism based on packet classification, and also utilizes fairly and efficiently assembly capacity. Based on token-bucket model and burst segment selective discard (BSSD), the offset-time scheme can smooth the traffic to support OBS QoS. The simulation results show that the technique can improve the performance in terms of packet loss probability (PLP).

A congestion alleviated scheme in optical burst switching network

An optical burst switching （OBS） network platform is established with a ring topology of three nodes. A congestion Mleviated scheme using advanced token protocol and wavelength tunable receivers is demon- strated to optimize the network platform. Experimental results testify that this scheme can resist collision at the level of 0.1% congestion rate.

Scalable and Practical Nonblocking Switching Networks

Large-scale strictly nonblocking （SNB） and wide-sense nonblocking （WSNB） networks may be infeasible due to their high cost. In contrast, rearrangeable nonblocking （RNB） networks are more scalable because of their much lower cost. However, RNB networks are not suitable for circuit switching. In this paper, the concept of virtual nonblockingness is introduced. It is shown that a virtual nonblocking （VNB） network functions like an SNB or WSNB network, but it is constructed with the cost of an RNB network. The results indicate that for large-scale circuit switching applications, it is only needed to build VNB networks.

A QoS-Guanranteed Scheduling Algorithm with High Throughput for Edge Nodes of Optical Burst Switching Networks

A scheduling algorithm for the edge nodes of optical burst switching (OBS) networks is proposed to guarantee the delay requirement of services with different CoS (Class of Service) and provide lower burst loss ratio at the same time. The performance of edge nodes based on the proposed algorithm is presented.

A new prediction method at the edge of optical burst switching network

To achieve lower assembly delay at optical burst switching edge node, this paper proposes an approach called current weight length prediction (CWLP) to improve existing estimate mechanism in burst assembly. CWLP method takes into account the arrived traffic in prediction time adequately. A parameter 'weight' is introduced to make a dynamic tradeoff between the current and past traffic under different offset time. Simulation results show that CWLP can achieve a significant improvement in terms of traffic estimation in various offset time and offered load.

A novel scheme based on minimum delay at the edges for optical burst switching networks

This paper proposes a novel scheme based on minimum delay at the edges (MDE) for optical burst switching (OBS) networks. This scheme is designed to overcome the long delay at the edge nodes of OBS networks. The MDE scheme features simultaneous burst assembly, channel scheduling, and pre-transmission of control packet. It also features estimated setup and explicit release (ESXR) signaling protocol. The MDE scheme can minimize the delay at the edge nodes for data packets, and improve the end-to-end latency performance for OBS networks. In addition, comparing with the conventional scheme, the performances of the MDE scheme are analyzed in this paper.

Analysis of a 32-Channal Benes Switching Network Including an SDM/WDM Router

An spatial division multiplexing/wavelength division multiplexing router is designed for applying in a fiber-optical wide area network. Our comparison shows various spans of the good SDM/WDM WAN using the SO A based router.

A New Approach to Implement Synchronous Demultiplexers in High-Speed ISDN Switching Network

This paper proves that a synchronous demultiplexer has the same logic function as a synchronous multiplexer. A new approach is proposed to implement synchronous demultiplexers in high-speed ISDN switching networks. A synchronous demultiplexer is designed utilizing the same structure as a synchronous shuffle multiplexer. Both the theoretical analysis and experimental results show that for the same capacity, the new method is more tolerant of signal delay variation, so a very high-speed synchronous demultiplexer can be designed with the larger capacity required in large capacity synchronous switching networks.

Improved adaptive-threshold burst assembly in optical burst switching networks

An improved adaptive-threshold burst assembly algorithm is proposed to alleviate the limitation of conventional assembly schemes on data loss and delay. The algorithm will adjust the values of assembly factors according to variant traffic regions. And the simulation results show that, by using the adaptive-factor adaptive assembly scheme, the performance of networks is extensively enhanced in terms of burst loss probability and average queuing delay.

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.

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.

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.

Event-Triggered Zero-Gradient-Sum Distributed Algorithm for Convex Optimization with Time-Varying Communication Delays and Switching Directed Topologies

Nowadays, distributed optimization algorithms are widely used in various complex networks. In order to expand the theory of distributed optimization algorithms in the direction of directed graph, the distributed convex optimization problem with time-varying delays and switching topologies in the case of directed graph topology is studied. The event-triggered communication mechanism is adopted, that is, the communication between agents is determined by the trigger conditions, and the information exchange is carried out only when the conditions are met. Compared with continuous communication, this greatly saves network resources and reduces communication cost. Using Lyapunov-Krasovskii function method and inequality analysis, a new sufficient condition is proposed to ensure that the agent state finally reaches the optimal state. The upper bound of the maximum allowable delay is given. In addition, Zeno behavior will be proved not to exist during the operation of the algorithm. Finally, a simulation example is given to illustrate the correctness of the results in this paper.

Stability of multiple fans in mine ventilation networks

In large mines,single fan is usually not enough to ventilate all the working areas.Single mine-fan approach cannot be directly applied to multiple-fan networks because the present of multiple pressures and air quantities associated with each fan in the network.Accordingly,each fan in a multiple-fan system has its own mine characteristic curve,or a subsystem curve.Under some consideration,the conventional concept of a mine characteristic curve of a single-fan system can be directly extended to that of a particular fan within a multiple-fan system.In this paper the mutual effect of the fans on each other and their effect on the stability of the ventilation network were investigated by Hardy Cross algorithm combined with a switching-parameters technique.To show the validity and reliability of this algorithm,the stability of the ventilation system of Abu-Tartur Mine(one of the largest underground mine in Egypt)has been studied.

Performance Analysis of DEBT Routing Protocols for Pocket Switch Networks

Pocket Switched Networks(PSN)represent a particular remittent network for direct communication between the handheld mobile devices.Compared to traditional networks,there is no stable topology structure for PSN where the nodes observe the mobility model of human society.It is a kind of Delay Tolerant Networks(DTNs)that gives a description to circulate information among the network nodes by the way of taking the benefit of transferring nodes from one area to another.Considering its inception,there are several schemes for message routing in the infrastructure-less environment in which human mobility is only the best manner to exchange information.For routing messages,PSN uses different techniques such asDistributed Expectation-Based Spatio-Temporal(DEBT)Epidemic(DEBTE),DEBT Cluster(DEBTC),and DEBT Tree(DEBTT).Understanding on how the network environment is affected for these routing strategies are the main motivation of this research.In this paper,we have investigated the impact of network nodes,the message copies per transmission,and the overall carrying out of these routing protocols.ONE simulator was used to analyze those techniques on the basis of delivery,overhead,and latency.The result of this task demonstrates that for a particular simulation setting,DEBTE is the best PSN routing technique among all,against DEBTC and DEBTT.

Implementing an Artificial Neural Network Computer

Based on the implementation of NNSPC (Neural NetWork Synchronous Parallel Computer) developed by NJU, this paper discusses two schemes for implementing artificial neural network computer withdistributed memories: One is Switch Network Structure; the other is Ring Topology Structure. This papergives a comparison betWeen the two schemes and the principles of scheme selection.

Network Resource Provisioning for IP over Multi-Granular Optical Networks

In the internet protocol（IP） over multi-granular optical switch network （IP/MG-OXC）, the network node is a typical multilayer switch comprising several layers, the IP packet switching （PXC） layer, wavelength switching （WXC） layer and fiber switching （FXC） layer. This network is capable of both IP layer grooming and wavelength grooming in a hierarchical manner. Resource provisioning in the multi-granular network paradigm is called hierarchical grooming problem. An integer linear programming （ILP） model is proposed to formulate the problem. An iterative heuristic approach is developed for solving the problem in large networks. Case study shows that IP/MG-OXC network is much more extendible and can significantly save the overall network cost as compared with IP over wavelength division multiplexing network.