• Title/Summary/Keyword: Network Optimization

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Rapid Self-Configuration and Optimization of Mobile Communication Network Base Station using Artificial Intelligent and SON Technology (인공지능과 자율운용 기술을 이용한 긴급형 이동통신 기지국 자율설정 및 최적화)

  • Kim, Jaejeong;Lee, Heejun;Ji, Seunghwan
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.9
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    • pp.1357-1366
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    • 2022
  • It is important to quickly and accurately build a disaster network or tactical mobile communication network adapting to the field. In configuring the traditional wireless communication systems, the parameters of the base station are set through cell planning. However, for cell planning, information on the environment must be established in advance. If parameters which are not appropriate for the field are used, because they are not reflected in cell planning, additional optimization must be carried out to solve problems and improve performance after network construction. In this paper, we present a rapid mobile communication network construction and optimization method using artificial intelligence and SON technologies in mobile communication base stations. After automatically setting the base station parameters using the CNN model that classifies the terrain with path loss prediction through the DNN model from the location of the base station and the measurement information, the path loss model enables continuous overage/capacity optimization.

Biogeography Based Optimization for Mobile Station Reporting Cell System Design (생물지리학적 최적화를 적용한 이동체 리포팅 셀 시스템 설계)

  • Kim, Sung-Soo
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.43 no.1
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    • pp.1-6
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    • 2020
  • Fast service access involves keeping track of the location of mobile users, while they are moving around the mobile network for a satisfactory level of QoS (Quality of Service) in a cost-effective manner. The location databases are used to keep track of Mobile Terminals (MT) so that incoming calls can be directed to requested mobile terminals at all times. MT reporting cell system used in location management is to designate each cell in the network as a reporting cell or a non-reporting cell. Determination of an optimal number of reporting cells (or reporting cell configuration) for a given network is reporting cell planning (RCP) problem. This is a difficult combinatorial optimization problem which has an exponential complexity. We can see that a cell in a network is either a reporting cell or a non-reporting cell. Hence, for a given network with N cells, the number of possible solutions is 2N. We propose a biogeography based optimization (BBO) for design of mobile station location management system in wireless communication network. The number and locations of reporting cells should be determined to balance the registration for location update and paging operations for search the mobile stations to minimize the cost of system. Experimental results show that our proposed BBO is a fairly effective and competitive approach with respect to solution quality for optimally designing location management system because BBO is suitable for combinatorial optimization and multi-functional problems.

A STUDY ON THE EFFICIENCY OF AERODYNAMIC DESIGN OPTIMIZATION IN DISTRIBUTED COMPUTING ENVIRONMENT (분산컴퓨팅 환경에서 공력 설계최적화의 효율성 연구)

  • Kim Y.J.;Jung H.J.;Kim T.S.;Son C.H.;Joh C.Y.
    • Journal of computational fluids engineering
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    • v.11 no.2 s.33
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    • pp.19-24
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    • 2006
  • A research to evaluate the efficiency of design optimization was carried out for aerodynamic design optimization problem in distributed computing environment. The aerodynamic analyses which take most of computational work during design optimization were divided into several jobs and allocated to associated PC clients through network. This is not a parallel process based on domain decomposition in a single analysis rather than a simultaneous distributed-analyses using network-distributed computers. GBOM(gradient-based optimization method), SAO(Sequential Approximate Optimization) and RSM(Response Surface Method) were implemented to perform design optimization of transonic airfoils and evaluate their efficiencies. dimensional minimization followed by direction search involved in the GBOM was found an obstacle against improving efficiency of the design process in the present distributed computing system. The SAO was found fairly suitable for the distributed computing environment even it has a handicap of local search. The RSM is apparently the most efficient algorithm in the present distributed computing environment, but additional trial and error works needed to enhance the reliability of the approximation model deteriorate its efficiency from the practical point of view.

Design Optimization of the Air Bearing Surface for the Optical Flying Bead (Optical Flying Head의 Air Bearing Surface 형상 최적 설계)

  • Lee Jongsoo;Kim Jiwon
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.2 s.233
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    • pp.303-310
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    • 2005
  • The systems with probe and SIL(Solid Immersion Lens) mechanisms have been researched as the technology to perform NFR(Near Field Recording). Most of them use the flying head mechanism to accomplish high recording density and fast data transfer rate. In this paper, ABS shape of flying head was optimized with the object of securing the maximum compliance ability of OFH. We suggest low different optimization processes to predict the static flying characteristics for the OFH. Two different approximation methods, regression analysis and back propagation neural network were used. And we compared the result of directly connected(between CAE and optimizer) method and two approximated optimization results. Design Optimization Tool(DOT) and ${\mu}GA$ were used as the optimizers.

On the Formulation and Optimal Solution of the Rate Control Problem in Wireless Mesh Networks

  • Le, Cong Loi;Hwang, Won-Joo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.5B
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    • pp.295-303
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    • 2007
  • An algorithm is proposed to seek a local optimal solution of the network utility maximization problem in a wireless mesh network, where the architecture being considered is an infrastructure/backbone wireless mesh network. The objective is to achieve proportional fairness amongst the end-to-end flows in wireless mesh networks. In order to establish the communication constraints of the flow rates in the network utility maximization problem, we have presented necessary and sufficient conditions for the achievability of the flow rates. Since wireless mesh networks are generally considered as a type of ad hoc networks, similarly as in wireless multi-hop network, the network utility maximization problem in wireless mesh network is a nonlinear nonconvex programming problem. Besides, the gateway/bridge functionalities in mesh routers enable the integration of wireless mesh networks with various existing wireless networks. Thus, the rate optimization problem in wireless mesh networks is more complex than in wireless multi-hop networks.

A study on the Algorithm for Mesh Network Topology Optimization and Routing (망토폴로지 최적화와 라우팅을 위한 알고리즘에 대한 연구)

  • Kim, Dong-Choon;Na, Seung-Kwon;Pyeon, Yong-Kug
    • Journal of Advanced Navigation Technology
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    • v.19 no.1
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    • pp.53-59
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    • 2015
  • We consider the problems that consist of designing time, establishment cost, delay time and reliability in designing a mesh network when given link costs and traffic requirements between nodes. Designing time, establishment cost and delay time are less, reliability is higher in designing a mesh network. One of the problems designing time is solved by mesh network topology optimization and routing (MENTOR) algorithm that Aaron Kershenbaum propose, but the others remain. In this paper we propose a new mesh network design algorithm with small computational complexity that the others are solved. The result of the proposed algorithm is better than MENTOR's in total establishment cost, delay time and reliability.

A FRAMEWORK FOR QUERY PROCESSING OVER HETEROGENEOUS LARGE SCALE SENSOR NETWORKS

  • Lee, Chung-Ho;Kim, Min-Soo;Lee, Yong-Joon
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.101-104
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    • 2007
  • Efficient Query processing and optimization are critical for reducing network traffic and decreasing latency of query when accessing and manipulating sensor data of large-scale sensor networks. Currently it has been studied in sensor database projects. These works have mainly focused on in-network query processing for sensor networks and assumes homogeneous sensor networks, where each sensor network has same hardware and software configuration. In this paper, we present a framework for efficient query processing over heterogeneous sensor networks. Our proposed framework introduces query processing paradigm considering two heterogeneous characteristics of sensor networks: (1) data dissemination approach such as push, pull, and hybrid; (2) query processing capability of sensor networks if they may support in-network aggregation, spatial, periodic and conditional operators. Additionally, we propose multi-query optimization strategies supporting cross-translation between data acquisition query and data stream query to minimize total cost of multiple queries. It has been implemented in WSN middleware, COSMOS, developed by ETRI.

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Analytic Determination of 3D Grasping points Using Neural Network (신경망을 이용한 3차원 잡는 점들의 해석적 결정)

  • 이현기;한창우;이상룡
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.4
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    • pp.112-117
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    • 2003
  • This paper deals with the problem of synthesis of the 3-dimensional Grasp Planning. In previous studies the genetic algorithm has been used to find optimal grasping points, but it had a limitation such as the determination time of grasping points was so long. To overcome this limitation we proposed a new algorithm which employs the Neural Network. In the Neural network we chose input parameters based on the shape of the object and output parameters resulted from optimization with the GA method. In this study the GRNN method is employed, it has been trained by the result value of optimization method and it has been tested by known object. The algorithm is verified by computer simulation.

Joint Radio Selection and Relay Scheme through Optimization Model in Multi-Radio Sensor Networks

  • Lee, HyungJune
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.12
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    • pp.4451-4466
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    • 2014
  • We present joint radio selection and relay scheme that delivers data from a source to a sink in heterogeneous stationary sensor networks consisting of various radio interfaces. The proposed scheme finds the optimal relay nodes and their corresponding radio interfaces that minimize energy consumption throughout the network while satisfying the end-to-end packet deadline requirement. We formulate the problem of routing through radio interface selection into binary integer programs, and obtain the optimal solution by solving with an optimization solver. We examine a trade-off relationship between energy consumption and packet delay based on network level simulations. We show that given the end-to-end deadline requirement, our routing algorithm finds the most energy-efficient routing path and radio interface across mesh hops. We demonstrate that the proposed routing scheme exploits the given packet delivery time to turn into network benefit of reducing energy consumption compared to routing based on single radio interface.

Optimal Bandwidth Assignment for Packet Rings

  • Hua, Cunqing;Yum, Tak-Shing Peter;Li, Cheng
    • Journal of Communications and Networks
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    • v.9 no.4
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    • pp.402-407
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    • 2007
  • The network throughput is an important performance criteria for the packet ring networks. Since maximizing the network throughput can lead to severe bias in bandwidth allocation among all flows, fairness should be imposed to prevent bandwidth starvation. The challenge here, therefore, is the joint optimization of the network throughput and fairness. In this paper, we present the optimal bandwidth assignment scheme to decompose this optimization problem into two tasks, one for finding fair bandwidth assignment and the other for finding the optimal routing. The network throughput is maximized under the fairness constraints when these tasks are performed iteratively.