• Title/Summary/Keyword: Operator Routing

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Design and Implementation of Location Utility Service for LBS

  • Kim, K.S.;Kim, J.C.;Lee, J.W.;Park, J.H.
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.849-851
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    • 2003
  • A location-based service or LBS in a cellular telephone network is a service provided to the subscriber based on his current geographic location. This position can be known by user entry or a GPS receiver that he carries with him, but most often the term implies the use of a function built into the cell network that uses the known geographic coordinates of the base stations through which the communication takes place. One implication is that knowledge of the coordinates is owned and controlled by the network operator, and not by the end user. Location utility service provides two kinds of functions, geocoder and reverse geocoder. Geocoder converts an address into a coordinate and reverse geocoder changes a coordinate into an address. Because location utility service is the first step to progress LBS, various servises such as directory, routing, presentation, and etc require to access that. In this paper, we will describe the architecture of LBS platform and the concept and the role of location utility service.

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Modified Genetic Operators for the TSP

  • Soak Sang Moon;Yang Yeon Mo;Lee Hong Girl;Ahn Byung Ha
    • Journal of Navigation and Port Research
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    • v.29 no.2
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    • pp.141-146
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    • 2005
  • For a long time, genetic algorithms have been recognized as a new method to solve difficult and complex problems and the performance of genetic algorithms depends on genetic operators, especially crossover operator. Various problems like the traveling salesman problem, the transportation problem or the job shop problem, in logistics engineering can be modeled as a sequencing problem This paper proposes modified genetic crossover operators to be used at various sequencing problems and uses the traveling salesman problem to be applied to a real world problem like the delivery problem and the vehicle routing problem as a benchmark problem Because the proposed operators use parental information as well as network information, they could show better efficiency in performance and computation time than conventional operators.

AP-SDN: Action Program enabled Software-Defined Networking Architecture

  • Zheng Zhao;Xiaoya Fan;Xin Xie;Qian Mao;Qi Zhao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.7
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    • pp.1894-1915
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    • 2023
  • Software-Defined Networking (SDN) offers several advantages in dynamic routing, flexible programmable control and custom application-driven network management. However, the programmability of the data plane in traditional SDN is limited. A network operator cannot change the ability of the data plane and perform complex packet processing on the data plane, which limits the flexibility and extendibility of SDN. In the paper, AP-SDN (Action Program enabled Software-Defined Networking) architecture is proposed, which extends the action set of SDN data plane. In the proposed architecture, a modified Open vSwitch is utilized in the data plane allowing the execution of action programs at runtime, thus enabling complex packet processing. An example action program is also implemented which transparently encrypts traffic for terminals. At last, a prototype system of AP-SDN is developed and experiments show its effectiveness and performance.

Estimation of ship operational efficiency from AIS data using big data technology

  • Kim, Seong-Hoon;Roh, Myung-Il;Oh, Min-Jae;Park, Sung-Woo;Kim, In-Il
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.12 no.1
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    • pp.440-454
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    • 2020
  • To prevent pollution from ships, the Energy Efficiency Design Index (EEDI) is a mandatory guideline for all new ships. The Ship Energy Efficiency Management Plan (SEEMP) has also been applied by MARPOL to all existing ships. SEEMP provides the Energy Efficiency Operational Indicator (EEOI) for monitoring the operational efficiency of a ship. By monitoring the EEOI, the shipowner or operator can establish strategic plans, such as routing, hull cleaning, decommissioning, new building, etc. The key parameter in calculating EEOI is Fuel Oil Consumption (FOC). It can be measured on board while a ship is operating. This means that only the shipowner or operator can calculate the EEOI of their own ships. If the EEOI can be calculated without the actual FOC, however, then the other stakeholders, such as the shipbuilding company and Class, or others who don't have the measured FOC, can check how efficiently their ships are operating compared to other ships. In this study, we propose a method to estimate the EEOI without requiring the actual FOC. The Automatic Identification System (AIS) data, ship static data, and environment data that can be publicly obtained are used to calculate the EEOI. Since the public data are of large capacity, big data technologies, specifically Hadoop and Spark, are used. We verify the proposed method using actual data, and the result shows that the proposed method can estimate EEOI from public data without actual FOC.