• Journal of Communications and Networks
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• v.12 no.3
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• pp.275-284
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• 2010

The current multihome-aware protocols (like stream control transmission protocol (SCTP) or parallel TCP for concurrent multipath data transfer (CMT) are not designed for high-capacity and large-latency networks; they often have performance problems transferring large data files over shared long-distance wide area networks. It has been shown that SCTP-CMT is more sensitive to receive buffer (rbuf) constraints, and this rbuf-blocking problem causes considerable throughput loss when multiple paths are used simultaneously. In this research paper, we demonstrate the weakness of SCTP-CMT rbuf constraints, and we then identify that rbuf-blocking problem in SCTP multihoming is mostly due to its loss-based nature for detecting network congestion. We present a simulation-based performance comparison of FAST TCP versus SCTP in high-speed networks for solving a number of throughput issues. This work proposes an end-to-end transport layer protocol (i.e., FAST TCP multihoming as a reliable, delaybased, multihome-aware, and selective ACK-based transport protocol), which can transfer data between a multihomed source and destination hosts through multiple paths simultaneously. Through extensive ns-2 simulations, we show that FAST TCP multihoming achieves the desired goals under a variety of network conditions. The experimental results and survey presented in this research also provide an insight on design decisions for the future high-speed multihomed transport layer protocols.

• ETRI Journal
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• v.44 no.5
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• pp.733-745
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• 2022

In software-defined wireless networking (SDWN), the optimal routing technique is one of the effective solutions to improve its performance. This routing technique is done by many different methods, with the most common using integer linear programming problem (ILP), building optimal routing metrics. These methods often only focus on one routing objective, such as minimizing the packet blocking probability, minimizing end-to-end delay (EED), and maximizing network throughput. It is difficult to consider multiple objectives concurrently in a routing algorithm. In this paper, we investigate the application of machine learning to control routing in the SDWN. An intelligent routing algorithm is then proposed based on the machine learning to improve the network performance. The proposed algorithm can optimize multiple routing objectives. Our idea is to combine supervised learning (SL) and reinforcement learning (RL) methods to discover new routes. The SL is used to predict the performance metrics of the links, including EED quality of transmission (QoT), and packet blocking probability (PBP). The routing is done by the RL method. We use the Q-value in the fundamental equation of the RL to store the PBP, which is used for the aim of route selection. Concurrently, the learning rate coefficient is flexibly changed to determine the constraints of routing during learning. These constraints include QoT and EED. Our performance evaluations based on OMNeT++ have shown that the proposed algorithm has significantly improved the network performance in terms of the QoT, EED, packet delivery ratio, and network throughput compared with other well-known routing algorithms.

• ETRI Journal
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• v.45 no.6
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• pp.963-973
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• 2023

Non-orthogonal multiple access (NOMA) is considered a key candidate technology for next-generation wireless communication systems due to its high spectral efficiency and massive connectivity. Incorporating the concepts of multiple-input-multiple-output (MIMO) into NOMA can further improve the system efficiency, but the hardware complexity increases. This study develops an energy-efficient (EE) subchannel assignment framework for MIMO-NOMA systems under the quality-of-service and interference constraints. This framework handles an energy-efficient co-training-based semi-supervised learning (EE-CSL) algorithm, which utilizes a small portion of existing labeled data generated by numerical iterative algorithms for training. To improve the learning performance of the proposed EE-CSL, initial assignment is performed by a many-to-one matching (MOM) algorithm. The MOM algorithm helps achieve a low complex solution. Simulation results illustrate that a lower computational complexity of the EE-CSL algorithm helps significantly minimize the energy consumption in a network. Furthermore, the sum rate of NOMA outperforms conventional orthogonal multiple access.

• Korean Journal of Cognitive Science
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• v.6 no.2
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• pp.97-116
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• 1995

This study was conducted to investigate how syntaction and pragmatic constraints influence the sentential representation and memory accessibility. In order to seperate the syntactic constraints from the pragmatic constraint from the pragmatic constraints,the syntactic role of constituent in the sentence (subject or object) and the order of mention(first or second) were manipulted.After each sentence was presented by RSVP procedure,the probe recognition time was measured to investigate memory accessibility.In Experiment 1,in which SOA interval was 255ms,it was found that the subject of a sentece were more accessible than the object and participants first in a sentence were more accessible than participants mentioned later.However, in Experiment 2,in which SOA interval was 1540ms,it was found that participants mentioned first in a sentence were more accessible than participants mentioned later while there was no significant difference between the subject and object of a sentece.These results suggest that the syntactic and pragmatic constraints have an independent effect on the initial senential representation at the early stage of constructing representation,but as time passes only the pragmatic constraints influence sentential representation.These results also support a theoretical position which assumes that sentential representation is constructed through the process of convergent statisfaction of multiple constraints.

• The Journal of the Korea Contents Association
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• v.17 no.12
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• pp.473-484
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• 2017

The purpose of this study was to examine the relationships among marketing mix, constraints, and consumers' revisiting intentions in screen sport theme parks. For this purpose, a survey was given to a convenience sample of 253 customers of screen sport theme parks located in the Seoul and Dae-gu metropolitan cities in South Korea. The data were then analyzed using frequency statistics, correlations, and multiple regression analysis. The major findings of this study were as follows. First, the marketing mix had a significant effect on the constraints of customers in screen sport theme parks. Second, the marketing mix had a significant effect on the revisiting intentions of customers in screen sport theme parks. Third, intrapersonal constraints alone had a significant effect on the revisiting intentions of customers in screen sport theme parks.

• The Journal of the Korea Contents Association
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• v.11 no.9
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• pp.459-468
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• 2011

This study was to analyze the relationship of leisure constraint, boredom and satisfaction among the private security agents. To attain the goal of this study, the employee of private security organization located in Seoul, 2011 year were sampled 400 peoples by purposive sampling method. The result of reliability check up was here below; over Cronbach's ${\alpha}$=.587. To analyze materials, reliability analysis, factor analysis, T test and F test, multiple regression analysis and path analysis were used as statistic analysis techniques. The conclusion are here below. First, leisure constraints, boredom and satisfaction have a difference in demographic and socio-economic characteristics. Second, leisure constraints influence on the leisure boredom. Third, leisure constraints influence on the leisure satisfaction. Fourth, leisure constraints influence directly, indirectly on leisure boredom and satisfaction. Leisure boredom is very important variable connecting leisure constraints and satisfaction.

• Journal of Aerospace System Engineering
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• v.17 no.2
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• pp.78-85
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• 2023

For Multi-UAV systems, a task allocation could be a key factor to determine the capability to perform a task. In this paper, we proposed a task allocation method based on genetic algorithm for minimizing makespan and satisfying various constraints. To obtain the optimal solution of the task allocation problem, a huge calculation effort is necessary. Therefore, a genetic algorithm-based method could be an alternative to get the answer. Many types of UAVs, tasks, and constraints in real worlds are introduced and considered when tasks are assigned. The proposed method can build the task sequence of each UAV and calculate waiting time before beginning tasks related to constraints. After initial task allocation with a genetic algorithm, waiting time is added to satisfy constraints. Multiple numerical simulation results validated the performance of this mission planning method with minimized makespan.

• Journal of KIISE:Software and Applications
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• v.35 no.4
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• pp.207-218
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• 2008

With the growth of the Internet, multimedia streaming becomes an important means to deliver video contents over the Internet and the amount of the streaming multimedia contents is also getting increased. However, it becomes difficult to guarantee the quality of service in real-time over the IP network environment with instantaneously varying bandwidth. In this paper, we propose an optimal adaptation framework for streaming contents over the Internet in the sense that the perceptual quality of the multi-angie content with multiple visual objects is maximized given the constraints such as available bandwidth and transcoding cost. In the multi-angle video service framework, the user can select his/her preferred alternate views among the given multiple video streams captured at different view angles for a same event. This enhanced experience often entails streaming problems in real-time over the network, such as instantaneous bandwidth changes in the Internet. In order to cope with this problem, we assume that multi-angle video contents are encoded at different bitrates and the appropriate video streams are then selected or transcoded for delivery to meet such bandwidth constraints. For the user selective consumption of the various bitstreams in the multi-angle video service, the bitstream in each angle can be encoded in various bitrate, and the user can select a sub-bitrstream in the given bitrstreams or transcode the corresponding content in order to deliver the optimally adapted video contents to the instantaneously changing network condition. Therefore, we define the transcoding cost which means the time taken for transcoding the video stream and formulate a unified optimization framework which maximizes the perceptual quality of the multiple video objects in the given constraints such as the transcoding cost and the network bandwidth. Finally, we present plenty of the experimental results to show the effectiveness of the proposed method.

• Journal of Communications and Networks
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• v.16 no.1
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• pp.36-44
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• 2014

Exploiting the energy-delay tradeoff for energy saving is critical for developing green wireless communication systems. In this paper, we investigate the delay-constrained energy-efficient packet transmission. We aim to minimize the energy consumption of multiple randomly arrived packets in an additive white Gaussian noise channel subject to individual packet delay constraints, by taking into account the practical on-off circuit power consumption at the transmitter. First, we consider the offline case, by assuming that the full packet arrival information is known a priori at the transmitter, and formulate the energy minimization problem as a non-convex optimization problem. By exploiting the specific problem structure, we propose an efficient scheduling algorithm to obtain the globally optimal solution. It is shown that the optimal solution consists of two types of scheduling intervals, namely "selected-off" and "always-on" intervals, which correspond to bits-per-joule energy efficiency maximization and "lazy scheduling" rate allocation, respectively. Next, we consider the practical online case where only causal packet arrival information is available. Inspired by the optimal offline solution, we propose a new online scheme. It is shown by simulations that the proposed online scheme has a comparable performance with the optimal offline one and outperforms the design without considering on-off circuit power as well as the other heuristically designed online schemes.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.61-73
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• 2000

The equilibrium network design problem can be formulated as a mathematical Program with variational inequality constraints. We know this problem may have may multiple local solutions due to its inherent characteristics - Nonlinear Objective function and Nonlinear, Nonconvex constraints. Hence, it is difficult to solve for a globally optimal solution. In this paper, we propose a genetic algorithm to obtain a globa1 optimum among many local optima. A Proposed a1gorithm is compared with 4 different solution algorithms for 1 small test network and 1 real-size network. The results of some computational testing are reported.