• Title/Summary/Keyword: network optimization

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Optimization of Air Quality Monitoring Networks in Busan Using a GIS-based Decision Support System (GIS기반 의사결정지원시스템을 이용한 부산 대기질 측정망의 최적화)

  • Yoo, Eun-Chul;Park, Ok-Hyun
    • Journal of Korean Society for Atmospheric Environment
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    • v.23 no.5
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    • pp.526-538
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    • 2007
  • Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

A Study on Interconnection Regime: Core Issues and Alternatives (국내 상호접속제도 연구: 핵심이슈와 대안 발굴)

  • Kim, Il-Jung;Shin, Minsoo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.40 no.4
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    • pp.678-691
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    • 2015
  • Internet and mobile traffic continues to surge exponentially in recent years due to popularization of smart devices, the appearance of various internet services carrying large amount of traffic from richer content and applications. This phenomenon leaded to various network problems such as the congestion delay, the non-balanced traffic ratio between ISPs, the continuous network investment cost and the Internet access problems. In light of changed data-driven communication ecosystem, There are growing concerns by both academia and industry that settlement-free peering and full transit regime have the limitations such as not only difficulties in maintaining mutual benefits but also difficulties in securing investment incentives for upgrading network performance and quality. Thus, it becomes more necessary for introducing the evolved internet interconnection regime which can fulfill the All-IP network environment. This study derives core issues regarding internet interconnection regime in Korea and suggest new evolved alternatives based on three point of view(traffic optimization, cost optimization, network investment optimization) through the empirical analysis.

Telecommunication Network Optimization Current Status and Challenges (통신망 최적화 연구 동향)

  • Park, Kyungchul;Lee, Heesang
    • Journal of Korean Institute of Industrial Engineers
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    • v.34 no.1
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    • pp.13-22
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    • 2008
  • This paper gives reviews on current research status in telecommunication network design. Two problems are identified as major research issues. One is the WDM network design problem, where traffic grooming, virtual topology design and routing and wavelength assignment problems are considered. The other is the OSPF weight setting problem which was proposed as a practical method to implement traffic engineering capability in IP networks. After presenting surveys on those problems, we discuss potential challenging research issues in telecommunication network design.

New learning algorithm to solve the inverse optimization problems

  • Aoyama, Tomoo
    • 제어로봇시스템학회:학술대회논문집
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    • 2002.10a
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    • pp.42.2-42
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    • 2002
  • We discuss a neural network solver for the inverse optimization problem. The problem is that find functional relations between input and output data, which are include defects. Finding the relations, predictions of the defect parts are also required. The part of finding the defects in the input data is an inverse problem . We consider the meanings to solve the problem on the neural network system at first. Next, we consider the network structure of the system, the learning scheme of the network, and at last, examine the precision on the numerical calculations. In the paper, we proposed the high-precision learning method for plural three-layer neural network system that is series-connect...

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Constellation Multi-Objective Optimization Design Based on QoS and Network Stability in LEO Satellite Broadband Networks

  • Yan, Dawei;You, Peng;Liu, Cong;Yong, Shaowei;Guan, Dongfang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.3
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    • pp.1260-1283
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    • 2019
  • Low earth orbit (LEO) satellite broadband network is a crucial part of the space information network. LEO satellite constellation design is a top-level design, which plays a decisive role in the overall performance of the LEO satellite network. However, the existing works on constellation design mainly focus on the coverage criterion and rarely take network performance into the design process. In this article, we develop a unified framework for constellation optimization design in LEO satellite broadband networks. Several design criteria including network performance and coverage capability are combined into the design process. Firstly, the quality of service (QoS) metrics is presented to evaluate the performance of the LEO satellite broadband network. Also, we propose a network stability model for the rapid change of the satellite network topology. Besides, a mathematical model of constellation optimization design is formulated by considering the network cost-efficiency and stability. Then, an optimization algorithm based on non-dominated sorting genetic algorithm-II (NSGA-II) is provided for the problem of constellation design. Finally, the proposed method is further evaluated through numerical simulations. Simulation results validate the proposed method and show that it is an efficient and effective approach for solving the problem of constellation design in LEO satellite broadband networks.

Study on Aerodynamic Optimization Design Process of Multistage Axial Turbine

  • Zhao, Honglei;Tan, Chunqing;Wang, Songtao;Han, Wanjin;Feng, Guotai
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • 2008.03a
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    • pp.130-135
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    • 2008
  • An aerodynamic optimization design process of multistage axial turbine is presented in this article: first, applying quasi-three dimensional(Q3D) design methods to conduct preliminary design and then adopting modern optimization design methods to implement multistage local optimization. Quasi-three dimensional(Q3D) design methods, which mainly refer to S2 flow surface direct problem calculation, adopt the S2 flow surface direct problem calculation program of Harbin Institute of Technology. Multistage local optimization adopts the software of Numeca/Design3D, which jointly adopts genetic algorithm and artificial neural network. The major principle of the methodology is that the successive design evaluation is performed by using an artificial neural network instead of a flow solver and the genetic algorithms may be used in an efficient way. Flow computation applies three-dimensional viscosity Navier Stokes(N-S) equation solver. Such optimization process has three features: (i) local optimization based on aerodynamic performance of every cascade; (ii) several times of optimizations being performed to every cascade; and (iii) alternate use of coarse grid and fine grid. Such process was applied to optimize a three-stage axial turbine. During the optimization, blade shape and meridional channel were respectively optimized. Through optimization, the total efficiency increased 1.3% and total power increased 2.4% while total flow rate only slightly changed. Therefore, the total performance was improved and the design objective was achieved. The preliminary design makes use of quasi-three dimensional(Q3D) design methods to achieve most reasonable parameter distribution so as to preliminarily enhance total performance. Then total performance will be further improved by adopting multistage local optimization design. Thus the design objective will be successfully achieved without huge expenditure of manpower and calculation time. Therefore, such optimization design process may be efficiently applied to the aerodynamic design optimization of multistage axial turbine.

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A Study on Mobile Wireless Communication Network Optimization Using Global Search Algorithm (전역 탐색 알고리듬을 이용한 이동 무선통신 네트워크의 최적화에 대한 연구)

  • 김성곤
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.1
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    • pp.87-93
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    • 2004
  • In the design of mobile wireless communication network, BSC(Base Station Location), BSC(Base Station Controller) and MSC(Mobile Switching Center) are the most important parameters. Designing base station location, the cost must be minimized by combining various, complex parameters. We can solve this Problem by combining optimization algorithm, such as Simulated Annealing, Tabu Search, Genetic Algorithm, Random Walk Algorithm that have been used extensively for global optimization. This paper shows the 4 kinds of algorithm to be applied to the optimization of base station location for communication system and then compares, analyzes the results and shows optimization process of algorithm.

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A Survey of Self-optimization Approaches for HetNets

  • Chai, Xiaomeng;Xu, Xu;Zhang, Zhongshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.6
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    • pp.1979-1995
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    • 2015
  • Network convergence is regarded as the development tendency of the future wireless networks, for which self-organization paradigms provide a promising solution to alleviate the upgrading capital expenditures (CAPEX) and operating expenditures (OPEX). Self-optimization, as a critical functionality of self-organization, employs a decentralized paradigm to dynamically adapt the varying environmental circumstances while without relying on centralized control or human intervention. In this paper, we present comprehensive surveys of heterogeneous networks (HetNets) and investigate the enhanced self-optimization models. Self-optimization approaches such as dynamic mobile access network selection, spectrum resource allocation and power control for HetNets, etc., are surveyed and compared, with possible methodologies to achieve self-optimization summarized. We hope this survey paper can provide the insight and the roadmap for future research efforts in the self-optimization of convergence networks.

A New Route Optimization Scheme for Network Mobility: Combining ORC Protocol with RRH and Using Quota Mechanism

  • Kong, Ruoshan;Feng, Jing;Gao, Ren;Zhou, Huaibei
    • Journal of Communications and Networks
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    • v.14 no.1
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    • pp.91-103
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    • 2012
  • Network mobility (NEMO) based on mobile IP version 6 has been proposed for networks that move as a whole. Route optimization is one of the most important topics in the field of NEMO. The current NEMO basic support protocol defines only the basic working mode for NEMO, and the route optimization problem is not mentioned. Some optimization schemes have been proposed in recent years, but they have limitations. A new NEMO route optimization scheme-involving a combination of the optimized route cache protocol (ORC) and reverse routing header (RRH) and the use of a quota mechanism for optimized sessions (OwR)-is proposed. This scheme focuses on balanced performance in different aspects. It combines the ORC and RRH schemes, and some improvements are made in the session selection mechanism to avoid blindness during route optimization. Simulation results for OwR show great similarity with those for ORC and RRH. Generally speaking, the OwR's performance is at least as good as that of the RRH, and besides, the OwR scheme is capable of setting up optimal routing for a certain number of sessions, so the performance can be improved and the cost of optimal routing in nested NEMO can be decreased.

Optimization of Design Variables of a Train Suspension Using Neural Network Model (신경회로망 모델을 이용한 철도 현가장치 설계변수 최적화)

  • 김영국;박찬경;황희수;박태원
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.7
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    • pp.542-549
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    • 2002
  • Computer simulation is essential to design the suspension elements of railway vehicle. By computer simulation, engineers can assess the feasibility of given design variables and chance them to get a bettor design. Even though commercial simulation codes are used, the computational time and cost remains non-trivial. Therefore, malty researchers have used a mesa model made by sampling data through simulation. In this paper, four mesa-models for each index group such as ride comfort, derailment Quotient, unloading radio and stability index, are constructed by use of neural network. After these meta models are constructed, multi-objective optimization are achieved by using the differential evolution. This paper shows that the optimization of design variables using the neural network model is very efficient to solve the complex optimization Problem.