• Fisheries and Aquatic Sciences
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• v.11 no.1
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• pp.61-69
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• 2008

Using empirical data of fish performance and physiological limits as well as physical stimuli and environmental data, a cod-end selectivity model based on a chaotic behavior model using the psycho-hydraulic wheel and neural-network approach was established to predict fish escape or herding responses in trawl and cod-end designs. Fish responses in the cod-end were categorized as escape or herding reactions based on their relative positions and reactions to the net wall. Fish movements were regulated by three factors: escape time, a visual looming effect, and an index of body girth-mesh size. The model was applied to haddock in a North Sea bottom trawl including frequencies of movement components, swimming speed, angular velocity, distance to net wall, and the caught-fish ratio; simulation results were similar to field observations. The ratio of retained fish in the cod-end was limited to 37-95% by optomotor coefficient values of 0.3-1.0 and to 13-67% by looming coefficient values of 0.1-1.0. The selectivity curves generated by this model were sensitive to changes in mesh size, towing speed, mesh type, and mesh shape.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2499-2522
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• 2017

Multi-hop networks are a low-setup-cost solution for enlarging an area of network coverage through multi-hop routing. Carrier sense multiple access with collision avoidance (CSMA/CA) is frequently used in multi-hop networks. Multi-hop networks face multiple problems, such as a rise in contention for the medium, and packet loss under heavy-load, saturated conditions, which consumes more bandwidth due to re-transmissions. The number of re-transmissions carried out in a multi-hop network plays a major role in the achievable quality of service (QoS). This paper presents a statistical, analytical model for the end-to-end delay of contention-based medium access control (MAC) strategies. These strategies schedule a packet before performing the back-off contention for both differentiated heterogeneous data and homogeneous data under saturation conditions. The analytical model is an application of Markov chain theory and queuing theory. The M/M/1 model is used to derive access queue waiting times, and an absorbing Markov chain is used to determine the expected number of re-transmissions in a multi-hop scenario. This is then used to calculate the expected end-to-end delay. The prediction by the proposed model is compared to the simulation results, and shows close correlation for the different test cases with different arrival rates.

• Journal of the Korea Society of Computer and Information
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• v.22 no.12
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• pp.95-100
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• 2017

In this paper, we propose a zone based ad hoc network construction scheme which support ad hoc path between nodes in local IoT networks consisting of IoT devices with the constrained feature, such as low power, the limited transmission rate and low computing capacity. Recently, the various routing protocols have been studied to support ad hoc networking of local IoT environments. This is, because basis RPL protocol is deigned to be used for the connecting service with Internet through gateway, ad hoc path between nodes in local IoT networks is not supported in basis RPL protocol. Thus, in this paper, the proposed routing scheme provides both ad hoc path and Infra path through gateway, supporting basis RPL protocol simultaneously. Through simulation, we show that the proposed routing scheme with zone based path selection scheme improves the performance of the success rate of end-to-end data transmission and the end-to-end delay, compared to basis RPL protocol.

• ETRI Journal
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• v.34 no.3
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• pp.462-465
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• 2012

This letter proposes a new distributed scheduling scheme combined with routing to support the quality of service of real-time applications in wireless mesh networks. Next, this letter drives average end-to-end delay of the proposed scheduling scheme that sequentially schedules the slots on a path. Finally, this letter simulates the time division multiple access network for performance comparison. From the simulation results, when the average number of hops is 2.02, 2.66, 4.1, 4.75, and 6.3, the proposed sequential scheduling scheme reduces the average end-to-end delay by about 28%, 10%, 17%, 27%, and 30%, respectively, compared to the conventional random scheduling scheme.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.180-187
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• 2002

Many real-time multimedia applications, such as video conferencing have stringent end-to-end delay constraints and consume large amount of network resources. In order to support these applications efficiently, multicast routing algorithms computing least cost multicast trees that satisfy a given end-to-end delay constraint are needed. However, finding such a tree is known to be computationally expensive. Therefore, we propose a heuristic distributed multicast routing algorithm that reduces a “finding multicast tree”that satisfies a given end-to-end delay constraint and minimizes the average resulting tree cost. Also, simulation results show that the proposed algorithm has much better average cost performance than other existing algorithms.

• Journal of Power Electronics
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• v.15 no.1
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• pp.202-215
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• 2015

This paper investigates the stability and performance of model predictive controlled active-front-end (AFE) rectifiers for energy storage systems, which has been increasingly applied in power distribution sectors and in renewable energy sources to ensure an uninterruptable power supply. The model predictive control (MPC) algorithm utilizes the discrete behavior of power converters to determine appropriate switching states by defining a cost function. The stability of the MPC algorithm is analyzed with the discrete z-domain response and the nonlinear simulation model. The results confirms that the control method of the active-front-end (AFE) rectifier is stable, and that is operates with an infinite gain margin and a very fast dynamic response. Moreover, the performance of the MPC controlled AFE rectifier is verified with a 3.0 kW experimental system. This shows that the MPC controlled AFE rectifier operates with a unity power factor, an acceptable THD (4.0 %) level for the input current and a very low DC voltage ripple. Finally, an efficiency comparison is performed between the MPC and the VOC-based PWM controllers for AFE rectifiers. This comparison demonstrates the effectiveness of the MPC controller.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.12
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• pp.5174-5190
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• 2016

Recent years have witnessed an explosive growth of mobile devices, mobile cloud computing services offered by these devices and the remote clouds behind them. In this paper, we noticed ultra-low latency service, as a type of mobile cloud computing service, requires extremely short delay constraints. Hence, such delay-sensitive applications should be satisfied with strong QoS guarantee. Existing solutions regarding this problem have poor performance in terms of throughput. In this paper, we propose an end-to-end bandwidth resource reservation via software defined scheduling inspired by the famous SDN framework. The main contribution of this paper is the end-to-end resource reservation and flow scheduling algorithm, which always gives priority to delay sensitive flows. Simulation results confirm the advantage of the proposed solution, which improves the average throughput of ultra-low latency flows.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.12
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• pp.1417-1422
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• 1991

In this paper we develop an analytic model for end-to-end communication protocols and study the window mechanism for flow control in store-and-forward computer networks. We develop a flow control model in which the parameters of the system are not dynamically adjusted to the stochastic fluctuation of the system load. Simulation results are presented and it is shown that the throughput-delay performance of a network can be improved by proper selection of the design parameter, such as timeout, the number of retransmission, etc.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.9
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• pp.227-234
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• 2018

Guaranteeing the end-to-end delay deadline is an important issue for quality of service (QoS) of delay sensitive systems, such as real-time system, networked control system (NCS), and cyber-physical system (CPS). Most routing algorithms typically use the mean end-to-end delay as a performance metric and select a routing path that minimizes it to improve average performance. However, minimum mean delay is an insufficient routing metric to reflect the characteristics of the unpredictable wireless channel condition because it only represents average value. In this paper, we proposes a deadline-aware routing algorithm that maximizes the probability of packet arrival within a pre-specified deadline for CPS by considering the delay distribution rather than the mean delay. The proposed routing algorithm constructs the end-to-end delay distribution in a given network topology under the assumption of the single hop delay follows an exponential distribution. The simulation results show that the proposed routing algorithm can enhance QoS and improve networked control performance in CPS by providing a routing path which maximizes the probability of meeting the deadline.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.41-45
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• 2019

In this paper, we propose the interference cancellation scheme of end-to-end method algorithm for power line communication (PLC) systems in smart grid. The proposed scheme estimates the channel noise information of receiver by applying a deep learning model at the receiver. Then, the estimated channel noise is updated in database. In the modulator, the channel noise which reduces the power line communication performance is effectively removed through interference cancellation technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the theoretical model based on additive white Gaussian noise. As a result, the proposed interference cancellation with deep learning improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC for smart grid and general communication systems.