• Title/Summary/Keyword: Optimized service

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Grid-based Location Service Spot scheme for optimized routing path on VANET (VANET 환경에서의 경로 최적화를 위한 그리드 기반 위치 정보 서비스 스팟 기법)

  • Kim, Jong-Hyun;Kim, Kee-Cheon;Jung, Woo-Young
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.9 no.1
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    • pp.76-90
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    • 2010
  • Location Service is required in position-based routing for VANET to provide position information. We propose Grid-based Location service spot(GLSS) scheme for optimized routing path to improve accessibility and load balance in location service. Specific area is defined as Location service spot(LSS) on each grid in this scheme, and all nodes in the grid geocast its location update message and location request message to each LSS. Location request messages are flooded throughout LSSs, location reply messages establish optimized route from the source grid to the destination grid. We evaluated GLSS which establishes optimized route on the grid comparing GPSR in consideration of road condition and geographical features.

Long-Term Container Allocation via Optimized Task Scheduling Through Deep Learning (OTS-DL) And High-Level Security

  • Muthakshi S;Mahesh K
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.17 no.4
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    • pp.1258-1275
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    • 2023
  • Cloud computing is a new technology that has adapted to the traditional way of service providing. Service providers are responsible for managing the allocation of resources. Selecting suitable containers and bandwidth for job scheduling has been a challenging task for the service providers. There are several existing systems that have introduced many algorithms for resource allocation. To overcome these challenges, the proposed system introduces an Optimized Task Scheduling Algorithm with Deep Learning (OTS-DL). When a job is assigned to a Cloud Service Provider (CSP), the containers are allocated automatically. The article segregates the containers as' Long-Term Container (LTC)' and 'Short-Term Container (STC)' for resource allocation. The system leverages an 'Optimized Task Scheduling Algorithm' to maximize the resource utilisation that initially inquires for micro-task and macro-task dependencies. The bottleneck task is chosen and acted upon accordingly. Further, the system initializes a 'Deep Learning' (DL) for implementing all the progressive steps of job scheduling in the cloud. Further, to overcome container attacks and errors, the system formulates a Container Convergence (Fault Tolerance) theory with high-level security. The results demonstrate that the used optimization algorithm is more effective for implementing a complete resource allocation and solving the large-scale optimization problem of resource allocation and security issues.

A Study on Optimized Size of a Mobile Harbor for South Korea Coastal Service

  • Heo, Sung-Kuk;Park, Nam-Kyu
    • Journal of Navigation and Port Research
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    • v.35 no.2
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    • pp.159-165
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    • 2011
  • The aim of paper is to calculate the optimized size of Mobile Harbor(MH) which would be operated in South Korea coast area. MH is the combined entity which has the function of both ship and container port. In estimating the optimized size, the total cost concept is applied to the different size of MH. Trade-off factors for calculating total cost are MH cost and the over-capacity lost cost. The factors for MH cost estimation are the cargo demand, distance from origin to destination, voyage route and MH's fixed and variable cost in both sailing and port. The other cost is the over-capacity lost cost which is occurred from dead space in case of oversize compared with a voyage demand. The alternatives for the least cost are 250TEU, 500TEU, 750TEU and 1,000TEU sized vessel. The result of research is that 250TEU sized vessel is optimized in a South Korea costal service. If the coastal area be separated in terms of voyage distance or the specific area in considering trade, the optimized size is changed depending upon distance.

Seamless Video Switching System for Service Compatible 3DTV Broadcasting

  • Kim, Sangjin;Jeon, Taehyun
    • ETRI Journal
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    • v.38 no.5
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    • pp.847-857
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    • 2016
  • Broadcasting services such as multi/single channel HDTV and 3DTV/2DTV use a multi-channel encoder that changes the bitrate and composition of the video service depending on the time. However, this type of multi-channel encoder could cause a longer latency owing to the variable bitrate and relatively bigger size of the buffers, which results in the same delay as in 3DTV even for a conventional DTV service. On the other hand, systems built based on separate encoders, each of which is optimized for the target service, might not have such latency problems. Nevertheless, there might be a distortion problem in the image and sound at the time of a switchover between two encoders with different output bitrates and group of picture structures. This paper proposes a system that can realize a seamless video service conversion using two different video encoders optimized for each video service. An overall functional description of the video service change control server, which is a main control block for the proposed system, is also provided. The experiment results confirm the seamless switchover and reduced broadcasting latency of DTV services compared with a broadcasting system composed of a multi-channel encoder system.

Design and Implementation of Optimized Route Search Technique based on User Experience Using Open APIs (지도 오픈 API를 활용한 사용자 경험 기반 최적화 이동 경로 탐색 기법의 설계와 구현)

  • Sagong, Woon
    • Journal of Korea Multimedia Society
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    • v.18 no.5
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    • pp.682-690
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    • 2015
  • Among location-based systems, a route search service is very highly utilized as a representative technique, but it provides relatively low accuracy when we find a route path on foot in our real environment. In this paper, we design and implement an optimized route search technique based on user experience utilizing open APIs as location-based services. Finally, we develop an Android-based application to provide this feature. In our experiment, we found that our technique enhanced performance by about 14-36% compared to previous solutions, such as route path searches using map APIs. In addition, the performance of our technique can be further enhanced, as the number of users who find such optimized route path is increasing.

Performance Evaluation of Recommendation Results through Optimization on Content Recommendation Algorithm Applying Personalization in Scientific Information Service Platform (과학 학술정보 서비스 플랫폼에서 개인화를 적용한 콘텐츠 추천 알고리즘 최적화를 통한 추천 결과의 성능 평가)

  • Park, Seong-Eun;Hwang, Yun-Young;Yoon, Jungsun
    • The Journal of the Korea Contents Association
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    • v.17 no.11
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    • pp.183-191
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    • 2017
  • In order to secure the convenience of information retrieval by users of scientific information service platforms and to reduce the time required to acquire the proper information, this study proposes an optimized content recommendation algorithm among the algorithms that currently provide service menus and content information for each service, and conducts comparative evaluation on the results. To enhance the recommendation accuracy, users' major items were added to the original algorithm, and performance evaluations on the recommendation results from the original and optimized algorithms were performed. As a result of this evaluation, we found that the relevance of the content provided to the users through the optimized algorithm was increased by 21.2%. This study proposes a method to shorten the information acquisition time and extend the life cycle of the results as valuable information by automatically computing and providing content suitable for users in the system for each service menu.

Trends in AI Processor Technology (인공지능프로세서 기술 동향)

  • Lee, M.Y.;Chung, J.;Lee, J.H.;Han, J.H.;Kwon, Y.S.
    • Electronics and Telecommunications Trends
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    • v.35 no.3
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    • pp.66-75
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    • 2020
  • As the increasing expectations of a practical AI (Artificial Intelligence) service makes AI algorithms more complicated, an efficient processor to process AI algorithms is required. To meet this requirement, processors optimized for parallel processing, such as GPUs (Graphics Processing Units), have been widely employed. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted. This paper briefly introduces an AI processor especially for inference acceleration, developed by the Electronics and Telecommunications Research Institute, South Korea., and other global vendors for mobile and server platforms. However, the GPU has a generalized structure for various applications, so it is not optimized for the AI algorithm. Therefore, research on the development of AI processors optimized for AI algorithm processing has been actively conducted.

Profile-based Service Continuity Framework for N-Screen Service

  • Chung, Young-Sik;Paik, Eui-Hyun;Rhee, Woo-Seop
    • International Journal of Contents
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    • v.8 no.1
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    • pp.47-54
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    • 2012
  • The dynamic adaptation between various service environments using the application profiles for the service continuity is a key issue of the profile-based service continuity framework (PSCF) for N-screen service using next generation networks. PSCF offers an optimized service framework for providing continuous user services, which are multimedia video streaming, educational broadcasting, game, etc., using the various devices that are not restricted by the service environment of the user. This paper specifies the functional model of PSCF, service scenario and explains the experimental results of the service continuity for N-screen service using PSCF.

Development of Preliminary Design Model for Ultra-Large Container Ships by Genetic Algorithm

  • Han, Song-I;Jung, Ho-Seok;Cho, Yong-Jin
    • International Journal of Ocean System Engineering
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    • v.2 no.4
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    • pp.233-238
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    • 2012
  • In this study, we carried out a precedent investigation for an ultra-large container ship, which is expected to be a higher value-added vessel. We studied a preliminary optimized design technique for estimating the principal dimensions of an ultra-large container ship. Above all, we have developed optimized dimension estimation models to reduce the building costs and weight, using previous container ships in shipbuilding yards. We also applied a generalized estimation model to estimate the shipping service costs. A Genetic Algorithm, which utilized the RFR (required freight rate) of a container ship as a fitness value, was used in the optimization technique. We could handle uncertainties in the shipping service environment using a Monte-Carlo simulation. We used several processes to verify the estimated dimensions of an ultra-large container ship. We roughly determined the general arrangement of an ultra-large container ship up to 1500 TEU, the capacity check of loading containers, the weight estimation, and so on. Through these processes, we evaluated the possibility for the practical application of the preliminary design model.