• International Journal of Reliability and Applications
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• v.9 no.1
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• pp.1-5
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• 2008

A heuristic algorithm for reliability optimization of a distributed network system is developed so that the reliability of a large system can be determined efficiently. This heuristic bases on the determination of maximal reliability set of maximum node capacity, maximal link reliability and maximal node degree.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.269-272
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• 2005

무선 네트워크 이동성 기술에 대한 연구가 수년간 진행되어 오면서 Mobile Network에 PAN(Personal Area Network)과 유사한 형태의 Nested Mobile Network에 대한 관심이 높아지고 있으며, 이러한 Nested Mobile Network에서의 경로최적화(Route Optimization : RO) 기술에 대한 연구가 활발하게 진행되고 있다. NEMO(NEtwork MObility)의 RO를 위해 제안된 논문 중에 ORC(Optimized Route Cache Protocol)에 대한 제안이 있었다.[1] NEMO Basic Support가 표준안으로 채택되면서 연구 대상에서 거론되지 않고 있지만, 복잡한 이동성 기술인 Nested Mobile Network상의 RO를 위해 다시 검토해 볼 수 있을 것이다. 또한 동일 저자에 의해 제안된 Nested Mobile Network 내부에 Ad-hoc Routing 알고리즘인 OLSR(Optimized Link State Routing Protocol)을 적용한 제안이 발표되었다.[2] 본 논문에서는 ORC와 Nested Mobile Network상의 OLSR Scheme을 적용하여 RO를 위한 방안을 제안하고자 한다.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.335-336
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• 2008

By using DM(Diagnostic Monitoring) data measured at WiBro network, automatic optimization function of WiBro network is implemented in this paper. The optimization function mentioned is able to be run on PC with 2GHz CPU and 1 GB memory. Automatic optimization function is one module of CellTREK that is a wireless network planning and optimization software developed by Infra Lab., KT.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.2800-2814
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• 2020

5G network optimization problem is a challenging optimization problem in the practical engineering applications. In this paper, to tackle this issue, Pareto fronts-driven Multi-Objective Cuckoo Search (PMOCS) is proposed based on Cuckoo Search. Firstly, the original global search manner is upgraded to a new form, which is aimed to strengthening the convergence. Then, the original local search manner is modified to highlight the diversity. To test the overall performance of PMOCS, PMOCS is test on three test suits against several classical comparison methods. Experimental results demonstrate that PMOCS exhibits outstanding performance. Further experiments on the 5G network optimization problem indicates that PMOCS is promising compared with other methods.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.46-54
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• 2023

To improve the railway transportation capacity and maximize the benefits of railway transportation, a method for layout optimization of railway transportation route based on deep convolution neural network is proposed in this study. Considering the transportation cost of railway transportation and other factors, the layout model of railway transportation route is constructed. Based on improved ant colony algorithm, the layout model of railway transportation route was optimized, and multiple candidate railway transportation routes were output. Taking into account external information such as regional information, weather conditions and actual information of railway transportation routes, optimization of the candidate railway transportation routes obtained by the improved ant colony algorithm was performed based on deep convolution neural network, and the optimal railway transportation routes were output, and finally layout optimization of railway transportation routes was realized. The experimental results show that the proposed method can obtain the optimal railway transportation route, the shortest transportation length, and the least transportation time, maximizing the interests of railway transportation enterprises.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.11 no.4
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• pp.9-17
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• 2007

Network Mobility basic support protocol (NEMO Basic) extends the operation of Mobile IPv6 to provide uninterrupted Internet connectivity to the communicating nodes of mobile networks. The protocol uses a mobile router (MR) in the mobile network to perform prefix scope binding updates with its home agent (HA) to establish a bi-directional tunnel between the HA and MR. This solution reduces location-update signaling by making network movements transparent to the mobile nodes (MNs) behind the MR. However, delays in data delivery and higher overheads are likely to occur because of sub-optimal routing and multiple encapsulation of data packets. To manage the mobility of the mobile network, it is important to minimize packet overhead, to optimize routing, and to reduce the volume of handoff signals over the nested mobile network. This paper proposes en aggregate router-assisted route optimization (ARARO) scheme for nested mobile networks support which introduces a local anchor router in order to localize handoff and to optimize routing. With ARARO, a mobile network node (MNN) behind a MR performs route optimization with a correspondent node (CN) as the MR sends a binding update message (BU) to aggregate router (AGR) via root-MR on behalf of all active MNNs when the mobile network moves. This paper describes the new architecture and mechanisms and provides simulation results which indicate that our proposal reduces transmission delay, handoff latency and signaling overhead. To evaluate the scheme, we present the results of simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.6
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• pp.2925-2948
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• 2019

In order to improve the utilization of irrigation water resources of greenhouse tomatoes, a water-saving irrigation decision-making model based on genetic optimization T-S fuzzy neural network is proposed in this paper. The main work are as follows: Firstly, the traditional genetic algorithm is optimized by introducing the constraint operator and update operator of the Krill herd (KH) algorithm. Secondly, the weights and thresholds of T-S fuzzy neural network are optimized by using the improved genetic algorithm. Finally, on the basis of the real data set, the genetic optimization T-S fuzzy neural network is used to simulate and predict the irrigation volume for greenhouse tomatoes. The performance of the genetic algorithm improved T-S fuzzy neural network (GA-TSFNN), the traditional T-S fuzzy neural network algorithm (TSFNN), BP neural network algorithm(BPNN) and the genetic algorithm improved BP neural network algorithm (GA-BPNN) is compared by simulation. The simulation experiment results show that compared with the TSFNN, BPNN and the GA-BPNN, the error of the GA-TSFNN between the predicted value and the actual value of the irrigation volume is smaller, and the proposed method has a better prediction effect. This paper provides new ideas for the water-saving irrigation decision in greenhouse tomatoes.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.4
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• pp.166-172
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• 2020

Video streaming application such as YouTube is one of the most popular mobile applications. To adjust the quality of video for available network bandwidth, a streaming server provides multiple representations of video of which bit rate has different bandwidth requirements. A streaming client utilizes an adaptive bit rate scheme to select a proper video representation that the network can support. The download behavior of video streaming client player is governed by several parameters such as maximum buffer size. Especially, the size of the maximum playback buffer in the client player can greatly affect the user experience. To tackle this problem, in this paper, we propose the maximum buffer size optimization according to available network bandwidth and buffer status. Our simulation study shows that our proposed buffer size optimization scheme successfully mitigates playback stalls while preserving the similar quality of streaming video compared to existing ABR schemes.

• Proceedings of the KSME Conference
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• 2001.11b
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• pp.365-370
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• 2001

In order to minimize unstable flow occurred at a multiblade fan/scroll system, optimal angle and shape of cut-off was determined by using two-dimensional turbulent fluid field analyses and neural network. The results of CFD analyses were used for learning as data of input and output of neural network. After learning neural network optimization process was accomplished for design variables, the angle and the shape of cut-off, in the design domain. As a result of optimization, the optimal angle and shape were obtained as 71 and 0.092 times the outer diameter of impeller, respectively, which are very similar values to previous studies. Finally, it was verified that the fluid field is very stable for optimal angle and shape of cut-off by two-dimensional CFD analysis.

• Journal of Information Processing Systems
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• v.19 no.1
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• pp.130-138
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• 2023

The traffic flow in an urban area is affected by the date, weather, and regional traffic flow. The existing methods are weak to model the dynamic road network features, which results in inadequate long-term prediction performance. To solve the problems regarding insufficient capacity for dynamic modeling of road network structures and insufficient mining of dynamic spatio-temporal features. In this study, we propose a novel traffic flow prediction framework called shared spatio-temporal attention convolution optimization network (SSTACON). The shared spatio-temporal attention convolution layer shares a spatio-temporal attention structure, that is designed to extract dynamic spatio-temporal features from historical traffic conditions. Subsequently, the graph optimization module is used to model the dynamic road network structure. The experimental evaluation conducted on two datasets shows that the proposed method outperforms state-of-the-art methods at all time intervals.