• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.9A
• /
• pp.1359-1371
• /
• 1999

In this paper, we propose an efficient explicit rate (ER) feedback switch algorithm for available bit rate (ABR) flow control. In order to improve the disadvantages of existing ER feedback switch algorithms with congestion avoidance, the proposed scheme adjusts the target utilization dynamically according to the queue length and its growth rate. also, we investigate the performance of the proposed switch algorithm and compare it with ERICA and NIST switches using simulation. Simulation results show that the proposed switch algorithm can control the cell emission rate of a source rapidly according to variations of available link bandwidth by using dynamic adaptation of target utilization. It also exhibits a better performance than the existing ER feedback switches in terms of queue length and link utilization.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.4 no.2
• /
• pp.307-312
• /
• 2000

Asynchronous transfer mode(ATM) is flexible to support the various multimedia communication services such as data, voice, and image by applying asynchronous time-sharing and statistical multiplexing techniques to the existing data communication. ATM service is categorized to CBR, VBR, UBR, and ABR according to characteristics of the traffic and a required service qualities. Among them, ABR service guarantees a minimal bandwidth and can transmit cells at a maximum transmission rate within the available bandwidth. To minimize the cell losses in transmission and switching, a feedback information in ATM network is used to control the traffic. In this paper, predictive control algorithms are proposed for the feedback information. When the feedback information takes a long propagation delay to the backward nodes, ATM switch can experience a congestion situation from the queue length increases, and a high queue length fluctuations in time. The control algorithms proposed in this paper provides predictive control model using slop changes of the queue length function and previous data of the queue lengths. Simulation shows the effectiveness result of the proposed control algorithms.

• Journal of Communications and Networks
• /
• v.8 no.1
• /
• pp.93-105
• /
• 2006

The domination of the Internet by TCP-based services has spawned many efforts to provide high network utilization with low loss and delay in a simple and scalable manner. Active queue management (AQM) algorithms attempt to achieve these goals by regulating queues at bottleneck links to provide useful feedback to TCP sources. While many AQM algorithms have been proposed, most suffer from instability, require careful configuration of nonintuitive control parameters, or are not practical because of slow response to dynamic traffic changes. In this paper, we propose a new AQM algorithm, hybrid random early detection (HRED), that combines the more effective elements of recent algorithms with a random early detection (RED) core. HRED maps instantaneous queue length to a drop probability, automatically adjusting the slope and intercept of the mapping function to account for changes in traffic load and to keep queue length within the desired operating range. We demonstrate that straightforward selection of HRED parameters results in stable operation under steady load and rapid adaptation to changes in load. Simulation and implementation tests confirm this stability, and indicate that overall performances of HRED are substantially better than those of earlier AQM algorithms. Finally, HRED control parameters provide several intuitive approaches to trading between required memory, queue stability, and response time.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1999.04a
• /
• pp.403-403
• /
• 1999

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.325-327
• /
• 2005

In this paper, we propose the design of active queue management (AQM) control system using the self-recurrent wavelet neural network (SRWNN). By regulating the queue length close to reference value, AQM can control the congestions in TCP network. The SRWNN is designed to perform as a feedback controller for TCP dynamics. The parameters of network are tunes to minimize the difference between the queue length of TCP dynamic model and the output of SRWNN using gradient-descent method. We evaluate the performances of the proposed AQM approach through computer simulations.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.12
• /
• pp.1273-1277
• /
• 2011

This paper proposes a control-based approach for duty cycle adaptation in wireless sensor networks. The proposed method, QCon, controls duty cycle through queue management in order to achieve high performance under variable traffic rates. To minimize energy consumption while meeting delay requirement, we design a feedback controller, which adapts the sleeping time according to dynamically changing traffic by constraining the queue length at a predetermined value. Based on control theory, we analyze the adaptive behavior of QCon and derive conditions for system stability. Results from asymptotic analysis and simulations indicate that QCon outperforms existing scheduling protocol by achieving more energy savings while satisfying delay requirement.

• Journal of Electrical Engineering and Technology
• /
• v.3 no.2
• /
• pp.285-291
• /
• 2008

Active Queue Management(AQM) has been widely used for congestion avoidance in Transmission Control Protocol(TCP) networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level, most of them are incapable of adequately adapting to TCP network dynamics due to TCP's non-linearity and time-varying stochastic properties. To alleviate these problems, we introduce an AQM technique based on a dynamic neural network using the Back-Propagation(BP) algorithm. The dynamic neural network is designed to perform as a robust adaptive feedback controller for TCP dynamics after an adequate training period. We evaluate the performances of the proposed neural network AQM approach using simulation experiments. The proposed approach yields superior performance with faster transient time, larger throughput, and higher link utilization compared to two existing schemes: Random Early Detection(RED) and Proportional-Integral(PI)-based AQM. The neural AQM outperformed PI control and RED, especially in transient state and TCP dynamics variation.

• Journal of the Institute of Electronics Engineers of Korea SC
• /
• v.37 no.5
• /
• pp.13-21
• /
• 2000

In this paper, we investigate the performance improvement by applying flow control to LonWorks-based network systems which support various communication media together with interpretable class of systems. To this end, we introduce a circular queue at each node of industrial network systems usually operated in open loop. Then we utilize the feedback information of the number of data in a queue, the data arriving interval in a queue and channel error to make the overall industrial network system in closed loop. We verify the improved performance of the network systems in view of throughput and fairness measures via the experimental results conducted in several field situation.

• Journal of Institute of Control, Robotics and Systems
• /
• v.7 no.11
• /
• pp.962-966
• /
• 2001

The major problem at a branch point for point-to-multipoint available bit rate(ABR) services in asynchronous transfer mode (ATM) networks is how to consolidate backward resource management(BRM) cells from each branch for a multicast connection. In this paper, we propose an efficient feedback consolidation algorithm based on an adaptive dynamic threshold(ADT) to eliminate the consolidation noise and the reduce the consolidation delay. The main idea of the ADT algorithm lies in that each branch point estimates the ABR traffic condition of the network through the virtual queue estimation and the transmission threshold of the queue level in branch points is adaptively controlled according to the estimation. Simulation results show that the proposed ADT algorithm can achieve a faster response in congestion status and a higher link utilization compared with the previous works.

• Management Science and Financial Engineering
• /
• v.2 no.1
• /
• pp.123-145
• /
• 1996

We consider a priority-based multiclass queue with probabilistic feed-back. There are J service stations. Each customer belongs to one of the several priority classes, and the customers of each class arrive at each station in a Poisson process. A single server serves queued customers on a priority basis with a nonpreemptive scheduling discipline. The customers who complete their services feed back to the system instantaneously and join one of the queues of the stations or depart from the system according to a given probability. In this paper, we propose a new method to simplify the analysis of these queueing systems. By the analysis of busy periods and regenerative processes, we clarify the underlying system structure, and systematically obtain the mean for the sojourn time, i.e., the time from the arrival to the departure from the system, of a customer at every station. The mean for the number of customers queued in each station at an arbitrary time is also obtained simultaneously.