When a massive network disruption occurs, repair of the damaged network takes time, and the recovery process involves multiple stages. We propose a fast and flow-controlled multi-stage network recovery method for determining the pareto-optimal recovery order of failed physical components reflecting the balance requirement between maximizing the total amount of traffic on all logical paths, called total network flow, and providing adequate logical path flows. The pareto-optimal problem is formulated by mixed integer linear programming (MILP). A heuristic algorithm, called the grouped-stage recovery (GSR), is also introduced to solve the problem when the problem formulated by MILP is computationally intractable in a large-scale failure. The effectiveness of the proposed method was numerically evaluated. The results show that the pareto-optimal recovery order can be determined from the balance between total network flow and adequate logical path flows, the allocated minimum bandwidth of the logical path can be drastically improved while maximizing total network flow, and the proposed method with GSR is applicable to large-scale failures because a nearly optimal recovery order with less than 10% difference rate can be determined within practical computation time.

Information networks are an important infrastructure and their resources are shared by many users. In order to utilize their resources efficiently, they should be controlled to prevent synchronization of user traffic. In addition, fairness among users must be assured. This paper discusses the framework of transmission rate control based on chaos. There are two different characteristics that coexist in chaos. One is that the state in the future is extremely sensitive to the initial condition. This makes it impossible to predict the future state at a fine level of detail. The other is the structural stability of macroscopic dynamics. Even if the state is uncertain on the microscopic scale, state dynamics on the macroscopic scale are stable. This paper proposes a novel framework of distributed hierarchical control of transmission rate by interpreting the coexistence of chaos as microscopic fairness of users and macroscopic stable utilization of networks.

Since video traffic has become a dominant flow component on the Internet, the Future Internet and New Generation Network must consider delay guarantees as a key feature in their designs. Using the stochastic network optimization, optimal control policies are designed for delay-constrained traffic in single-hop wireless networks. The resulting policy is a scheduling policy with delay guarantees. For a cross-layer design that involves both flow control and scheduling, the resulting policy is a flow control and scheduling policy that guarantees delay constraints and achieves utility performance within O(1/V) of the optimality.

Stream Control Transmission Protocol (SCTP) is a new transport layer protocol for the next generation Internet. SCTP is a connection-oriented protocol that carries over TCP's features but also supports UDP-like message-oriented data transmission. In this paper, we make use of SCTP's multi-streaming feature to transmit MPEG-4 video efficiently, and evaluate its transmission performance under the policy with/without differentiated retransmission. Moreover, to enhance the communication quality, we extend SCTP multi-streaming to realize selective retransmission policy. Our extension utilizes packet-by-packet timestamps to control retransmission of lost packets. By computer simulation, we show that SCTP can (1) improve the video quality by exploiting the multi-streaming and partial reliability features, (2) enhance the video transmission quality by adjusting SCTP fast retransmit threshold, and (3) SCTP with our selective retransmission extension can further improve the whole performance.

Credit-based router-to-router flow control is one main link-level flow control mechanism proposed for Networks on Chip (NoCs). Based on network calculus, we analyze its performance and optimal buffer size. To model the feedback control behavior due to credits, we introduce a virtual network service element called flow controller. Then we derive its service curve, and further the system service curve. In addition, we give and prove a theorem that determines the optimal buffer size guaranteeing the maximum system service curve. Moreover, assuming the latency-rate server model for routers, we give closed-form formulas to calculate the flit delay bound and optimal buffer size. Our experiments with real on-chip traffic traces validate that our analysis is correct; delay bounds are tight and the optimal buffer size is exact.

The emergence of Web 2.0 technologies such as Ajax and Mashup has revealed the weakness of the same-origin policy [1], the current de facto standard for the Web browser security model. We propose a new browser security model to allow fine-grained access control in the client-side Web applications for secure mashup and user-generated contents. We propose a browser security model that is based on information-flow-based access control (IBAC) to overcome the dynamic nature of the client-side Web applications and to accurately determine the privilege of scripts in the event-driven programming model.

Based on the traffic predictability characteristic of Networks-on-Chip (NoC), we propose a pre-allocation based flow control scheme to improve the performance of NoC. In this scheme, routes are pre-allocated and the injection rates of all routes are regulated at the traffic sources according to the average available bandwidths in the links. Then, the number of packets in the network is decreased and thus, the congestion probability is reduced and the communication performance is improved. Simulation results show that this scheme greatly increases the throughput and cuts down the average latency with little area and energy overhead, compared with the switch-to-switch flow control scheme.

We have previously proposed a diffusion-type flow control mechanism as a solution for severely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow using the basis of only the local information directly available to it, by using predetermined rules. In addition, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies show that our flow control mechanism with certain parameter settings works well in high-speed networks. However, to apply this mechanism to actual networks, it is necessary to clarify how to design a parameter in our control mechanism. In this paper, we investigate the range of the parameter and derive its optimal value enabling the diffusion-type flow control to work effectively.

A Lyapunov-based recurrent neural networks unified power flow controller (UPFC) is developed for improving transient stability of power systems. First, a simple UPFC dynamical model, composed of a controllable shunt susceptance on the shunt side and an ideal complex transformer on the series side, is utilized to analyze UPFC dynamical characteristics. Secondly, we study the control configuration of the UPFC with two major blocks: the primary control, and the supplementary control. The primary control is implemented by standard PI techniques when the power system is operated in a normal condition. The supplementary control will be effective only when the power system is subjected by large disturbances. We propose a new Lyapunov-based UPFC controller of the classical single-machine-infinite-bus system for damping enhancement. In order to consider more complicated detailed generator models, we also propose a Lyapunov-based adaptive recurrent neural network controller to deal with such model uncertainties. This controller can be treated as neural network approximations of Lyapunov control actions. In addition, this controller also provides online learning ability to adjust the corresponding weights with the back propagation algorithm built in the hidden layer. The proposed control scheme has been tested on two simple power systems. Simulation results demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.

Optical Burst Switching (OBS) is one of the most promising switching technologies for next generation optical networks. As delay-sensitive applications such as Voice-over-IP (VoIP) have recently become popular, OBS networks should guarantee stringent Quality of Service (QoS) requirements for such applications. Thus, this paper proposes an Adaptive Loss-aware Flow Control (ALFC) scheme, which adaptively decides on the burst offset time based on loss-rate information delivered from core nodes for assigning a high priority to delay-sensitive application traffic. The proposed ALFC scheme also controls the upper-bounds of the factors inducing delay and jitter for guaranteeing the delay and jitter requirements of delay-sensitive application traffic. Moreover, a piggybacking method used in the proposed scheme accelerates the guarantee of the loss, delay, and jitter requirements because the response time for flow control can be extremely reduced up to a quarter of the Round Trip Time (RTT) on average while minimizing the signaling overhead. Simulation results show that our mechanism can guarantee a 10-3 loss-rate under any traffic load while offering satisfactory levels of delay and jitter for delay-sensitive applications.

Reliable end-to-end delivery service is one of the most important issues for wireless sensor networks in large-scale deployments. In this paper, a reliable data transport protocol, called the Data Forwarding Protocol (DFP), is proposed to improve the end-to-end delivery rate with minimum transport overhead for recovering from data loss in large-scale wireless sensor environments consisting of low speed mobile sensor nodes. The key idea behind this protocol is the establishment of multi-split connection on an end-to-end route, through the Agent Host (AH), which plays the role of a virtual source or a sink node. In addition, DFP applies the local error control and the local flow control mechanisms to multi-split connections, according to network state. Extensive simulations are carried out via ns-2 simulator. The simulation results demonstrate that DFP not only provide up to 30% more reliable data delivery, but also reduces the number of retransmission generated by data loss, compared with the TCP-like end-to-end approach.

We have proposed a diffusion-type flow control mechanism to achieve the extremely time-sensitive flow control required for high-speed networks. In this mechanism, each node in a network manages its local traffic flow only on the basis of the local information directly available to it, by using predetermined rules. In this way, the implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies concentrated on the flow control for a single flow. In this paper, we propose a diffusion-type flow control mechanism for multiple flows. The proposed scheme enables a network to quickly recover from a state of congestion and to achieve fairness among flows.

In current IP-based networks, the application of window-based end-to-end flow control, including TCP, to ensure reliable flows is an essential factor. However, since such a flow control is provided by the end hosts, end-to-end control cannot be applied to decision-making in a time-scale shorter than the round-trip delay. We have previously proposed a diffusion-type flow control mechanism to realize the extremely time sensitive flow control that is required for high-speed networks. In this mechanism, each network node manages its own traffic only on the basis of the local information directly available to it, by using predetermined rules. The implementation of decision-making at each node can lead to optimal performance for the whole network. Our previous studies showed that the mechanism works well, by itself, in high-speed networks. However, to apply this mechanism to actual networks, it needs to be able to coexist with other existing protocols. In this paper, we investigate the performance of diffusion-type flow control coexisting with TCP. We show that diffusion-type flow control can coexist with TCP and the two can be complementary. Then, we show that a combination of both controls achieves higher network performance than TCP alone in high-speed networks.

The proposed zero-current switching switched-capacitor (ZCS SC) DC-DC converter is an innovative bi-directional power flow control conversion scheme. A zero-current switching switched-capacitor step-up/step-down bi-directional converter is presented that can improve the current stress problem during bi-directional power flow control processing. It can provide a high voltage conversion ratio of n/ (n-mode/-mode) using four power MOSFET main switches, a set of switched-capacitors and a small resonant inductor. Simulation and experimental results are carried out to verify the concept and performance of the proposed quadruple-mode/quarter-mode bi-directional DC-DC converter.

This paper describes an analytical framework for the weighted max-min flow control of elastic flows in packet networks using PID and PII2 controller when flows experience heterogeneous round-trip delays. Our algorithms are scalable in that routers do not need to store any per-flow information of each flow and they use simple first come first serve (FCFS) discipline, stable in that the stability is proven rigorously when there are flows with heterogeneous round-trip delays. We first suggest two closed-loop system models that approximate our flow control algorithms in continuous-time domain where the purpose of the first algorithm is to achieve the target queue length and that of the second is to achieve the target utilization. The slow convergence [1] of many rate-based flow control algorithms, which use queue lengths as input signals, can be resolved by the second algorithm. Based on these models, we find the conditions for controller gains that stabilize closed-loop systems when round-trip delays are equal and extend this result to the case of heterogeneous round-trip delays with the help of Zero exclusion theorem. We simulate our algorithms with optimal gain sets for various configurations including a multiple bottleneck network to verify the usefulness and extensibility of our algorithms.

We have proposed diffusion-type flow control as a solution for the extremely time-sensitive flow control required for high-speed networks. In our method of flow control, we design in advance simple and appropriate rules for action at the nodes, and these automatically result in stable and efficient network-wide performance through local interactions between nodes. Specifically, we design the rules for the flow control action of each node that simulates the local interaction of a diffusion phenomenon, in order that the packet density is diffused throughout the network as soon as possible. However, in order to make a comparison with other flow control methods under the same conditions, the evaluations in our previous studies used a closed network model, in which the number of packets was unchanged. This paper investigates the performance of our flow control method for an end-to-end flow, in order to show that it is still effective in more realistic networks. We identify the key issues associated with our flow control method when applied to an open network model, and demonstrate a two-step solution. First, we consider the rule for flow control action at the boundary node, which is the ingress node in the network, and propose a rule to achieve smooth diffusion of the packet density. Secondly, we introduce a shaping mechanism, which keeps the number of packets in the network at an appropriate level.

This paper presents a new framework for traffic flow control based on an integrated model description by means of Hybrid Dynamical System (HDS). The geometrical information on the traffic network is characterized by Hybrid Petri Net (HPN). Then, the algebraic behavior of traffic flow is transformed into Mixed Logical Dynamical Systems (MLDS) form in order to introduce an optimization technique. These expressions involve both continuous evolution of traffic flow and event driven behavior of traffic signal. HPN allows us to easily formulate the problem for complicated and large-scale traffic network due to its graphical understanding. MLDS enables us to optimize the control policy for traffic signal by means of its algebraic manipulability and use of model predictive control framework. Since the behavior represented by HPN can be directly transformed into corresponding MLDS form, the seamless incorporation of two different modeling schemes provide a systematic design scenario for traffic flow control.

Available Bit Rate (ABR) flow control is an effective measure in ATM network congestion control. In large scale and high-speed network, the simplicity of algorithm is crucial to optimize the switch performance. Although the binary flow control is very simple, the queue length and allowed cell rate (ACR) controlled by the standard EFCI algorithm oscillate with great amplitude, which has negative impact on the performance, so its applicability was doubted, and then the explicit rate feedback mechanism was introduced and explored. In this study, the model of binary flow control is built based on the fluid flow theory, and its correctness is validated by simulation experiments. The linear model describing the source end system how to regulate the cell rate is obtained through local linearization method. Then, we evaluate and analyze the standard EFCI algorithm using the describing function approach, which is well-developed in nonlinear control theory. The conclusion is that queue and ACR oscillations are caused by the inappropriate nonlinear control rule originated from intuition, but not intrinsic attribute of the binary flow control mechanism. The simulation experiments validate our analysis and conclusion. Finally, the new scheme about parameter settings is put forward to remedy the weakness existed in the standard EFCI switches without any change on the hardware architecture. The numerical results demonstrate that the new scheme is effective and fruitful.

Recent growth in computer communications has led to an increased requirement for high-speed backbone networks. In such high-speed networks, the principle adopted for a time-sensitive flow control mechanism should be that of autonomous decentralized control. In this mechanism, each node in a network manages its local traffic flow only on the basis of the local information directly available to it, although it is desirable that the individual decisions made at each node lead to high performance of the network as a whole. In our previous studies, we have investigated the behavior of local packet flows and the global performance achieved when a node is congested, and proposed the diffusion-type flow control model. However, since we used a simple and homogeneous network model in the evaluation, the results cannot be generalized. In this paper, we propose an extension of the diffusion-type flow control model in order to apply it to networks with inhomogeneous configurations. We show simulation results for two cases: different propagation delays and multiple bottlenecks. Both results show that the proposed diffusion-type flow control achieves high and stable performance even if the network is congested.

This paper focuses on flow control in high-speed networks. Each node in a network handles its local traffic flow on the basis of only the information it is aware of, but it is preferable that the decision-making of each node leads to high performance of the whole network. To this end, we investigate the relationship between the flow control mechanism of each node and network performance. We consider the situation in which the capacity of a link in the network is changed but individual nodes are not aware of this. Then we investigate the stability and adaptability of the network performance, and discuss an appropriate flow control model on the basis of simulation results.