• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12A
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• pp.1226-1237
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• 2007

This paper proposes QoS mesh routing protocol for IEEE 802.16 based wireless mesh networks. QoS mesh routing protocol proposed in this paper is a proactive hop-by-hop QoS routing protocol. The goal of our routing protocol is not only to find a route from a source to a destination, but also optimal route that satisfies QoS requirements, given in terms of bandwidth and delay as default QoS parameters. In this paper, we first analyze possible types of routing protocols that have been studied for MANET and show proactive hop-by-hop routing protocols are the most appropriate for wireless mesh networks. Then, we present a network model for IEEE 802.16 based wireless mesh networks and propose a proactive hop-by-hop QoS routing protocol. Through our simulation, we represent that our routing protocol outperforms QOLSR protocol in terms of end-to-end delay, packet delivery ratio and routing overhead.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.1 no.1
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• pp.52-57
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• 2002

A simulation tool for an optimal ATIS design and drivers' dynamic route choice behavior analysis is developed, which is applicable to urban networks. Due to the difficulty to make drivers feel the time pressure according to traffic conditions, current SP questionnaire survey type surveys have a limitation to capture correct driver reactions to real-time traffic Information provision. The simulator Is a web-based upgraded version, named WATiSim (Web-based ATIS Simulator), to quickly perform a wide population survey with a minimal cost using INTERNET Furthermore, the time pressure issue is lessened by its interface and simulation modules. After WATiSim mimicked a VMS based ATIS in a partial network of Seoul Metropolitan, reactions of drivers to various traffic conditions were surveyed through INTERNET and analyzed using a logit model. Drivers under the ATIS environment clearly understood the provided traffic information, and their reactions were closely related to traffic conditions, scheduled delay, trip purposes as well as toll charge if any.

• Journal of Korea Water Resources Association
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• v.51 no.5
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• pp.383-393
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• 2018

The regional frequency analysis is the method which uses not only sample of target station but also sample of neighborhood stations in which are classified as hydrological homogeneous regions. Consequently, identification of homogeneous regions is a very important process in regional frequency analysis. In this study, homogeneous regions for regional frequency analysis of precipitation were identified by the self-organizing map (SOM) which is one of the artificial neural network. Geographical information and hourly rainfall data set were used in order to perform the SOM. Quantization error and topographic error were computed for identifying the optimal SOM map. As a result, the SOM model organized by $7{\times}6$ array with 42 nodes was selected and the selected stations were classified into 6 clusters for rainfall regional frequency analysis. According to results of the heterogeneity measure, all 6 clusters were identified as homogeneous regions and showed more homogeneous regions compared with the result of previous study.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.433-440
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• 2014

In this study, a method for the low-carbon active distribution system (ADS) planning is proposed. It takes into account the impacts of both network capacity and demand correlation to the renewable energy accommodation, and incorporates demand response (DR) as an available resource in the ADS planning. The problem is formulated as a mixed integer nonlinear programming model, whereby the optimal allocation of renewable energy sources and the design of DR contract (i.e. payment incentives and default penalties) are determined simultaneously, in order to achieve the minimization of total cost and $CO_2$ emissions subjected to the system constraints. The uncertainties that involved are also considered by using the scenario synthesis method with the improved Taguchi's orthogonal array testing for reducing information redundancy. A novel cuckoo search (CS) is applied for the planning optimization. The case study results confirm the effectiveness and superiority of the proposed method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.538-541
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• 2006

Recently researches of P2P media streaming have been actively published, but the research what kind of P2P overlay networks are better to delivering media data has not been attended. This paper designs a P2P streaming media system model. In this system, we constructs a Half-Structure P2P overlay protocol based on node's capability as the infrastructure of streaming application, which utilizes the heterogeneity of the nodes to maintain topology, presents a active contents diffusing algorithm and Two-stage search algorithm, make it possible for nodes in P2P system to collect information according their capacity and reduces the number of forwarding packet compared with flooding. Also, we give an optimal scheme to scheduling media data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2496-2512
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• 2021

The requirements for powerful computing capability, high capacity, low latency and low energy consumption of emerging services, pose severe challenges to the fifth-generation (5G) network. As a promising paradigm, mobile edge networks can provide services in proximity to users by deploying computing components and cache at the edge, which can effectively decrease service delay. However, the coexistence of heterogeneous services and the sharing of limited resources lead to the competition between various services for multiple resources. This paper considers two typical heterogeneous services: computing services and content delivery services, in order to properly configure resources, it is crucial to develop an effective offloading and caching strategies. Considering the high energy consumption of 5G base stations, this paper considers the hybrid energy supply model of traditional power grid and green energy. Therefore, it is necessary to design a reasonable association mechanism which can allocate more service load to base stations rich in green energy to improve the utilization of green energy. This paper formed the joint optimization problem of computing offloading, caching and resource allocation for heterogeneous services with the objective of minimizing the on-grid power consumption under the constraints of limited resources and QoS guarantee. Since the joint optimization problem is a mixed integer nonlinear programming problem that is impossible to solve, this paper uses deep reinforcement learning method to learn the optimal strategy through a lot of training. Extensive simulation experiments show that compared with other schemes, the proposed scheme can allocate resources to heterogeneous service according to the green energy distribution which can effectively reduce the traditional energy consumption.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.14 no.4
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• pp.163-181
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• 2004

Group key agreement protocols are designed to solve the fundamental problem of securely establishing a session key among a group of parties communicating over a public channel. Although a number of protocols have been proposed to solve this problem over the years, they are not well suited for a high-delay wide area network; their communication overhead is significant in terms of the number of communication rounds or the number of exchanged messages, both of which are recognized as the dominant factors that slow down group key agreement over a networking environment with high communication latency. In this paper we present a communication-efficient group key agreement protocol and prove its security in the random oracle model under the factoring assumption. The proposed protocol provides perfect forward secrecy and requires only a constant number of communication rounds for my of group rekeying operations, while achieving optimal message complexity.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.50-55
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• 2021

Multi-path system is a system in which utilizes various networks simultaneously. It is expected that multi-path system can enhance communication speed, reliability, security of network. In this paper, we focus on path selection in multi-path system. To select optimal path, we propose deep reinforcement learning algorithm which is rewarded by the round-trip-time (RTT) of each networks. Unlike multi-armed bandit model, deep Q learning is applied to consider rapidly changing situations. Due to the delay of RTT data, we also suggest compensation algorithm of the delayed reward. Moreover, we implement testbed learning server to evaluate the performance of proposed algorithm. The learning server contains distributed database and tensorflow module to efficiently operate deep learning algorithm. By means of simulation, we showed that the proposed algorithm has better performance than lowest RTT about 20%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1202-1208
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• 2020

In line with the current era of the 4th Industrial Revolution, it is necessary to prepare for the future by integrating AI elements in the ship sector. In addition, it is necessary to respond to this in the field of power management for the appearance of autonomous ships. In this study, we propose a battery-linked electric propulsion system (BLEPS) algorithm using machine learning's DNN. For the experiment, we learned the pattern of ship power consumption for each operation mode based on the ship data through LabView and derived the battery status through Python to check the flexibility of the generator and battery interlocking. As a result of the experiment, the low load operation of the generator was reduced through charging and discharging of the battery, and economic efficiency and reliability were confirmed by reducing the fuel consumption of 1% of LNG.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.1-12
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• 2021

Optimal water management is to efficiently and equally supply an appropriate amount of water by using irrigation facilities. Therefore, it is necessary to evaluate water supply capacity through distribution simulation between the designed distribution rate and re-distributed rate according to the changed farming conditions. In this study, we recalculated the agricultural water supply amount of Geumcheon main canal, which beneficiary area was reduced due to the development of Gwangju-Jeonnam innovation city, and we constructed a canal network using the SWMM model to simulate the change in supply rate of each main canal according to the re-distributed rate. Even though the supply amount of the Geumcheon main canal was reduced from 1.20 m³/s to 0.90 m³/s, it showed a similar supply rate to the current, and the reduced quantity could be supplied to the rest of the main canal. As a result, the arrival time at the ends of all main canal, except for the Geumcheon main canal, decreased from 1 to 3 hours, and the supply rate increased from 4 to 17.0% at the main canal located at the end of the beneficiary area of Naju reservoir.