• Title/Summary/Keyword: CAS Personalization

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A Mechanism of CAS Client Personalization through separating CAS Service of Protocol A.1 on TTA.KO-07.0079 XCAS (TTA.KO-07.0079 XCAS 프로토콜 A.1의 CAS 서비스 분리를 통한 CAS Client 개인화 메커니즘)

  • Kim, Young-Mo;Jang, Eun-Gyeom;Choi, Yong-Rak
    • Journal of the Korea Society of Computer and Information
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    • v.15 no.11
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    • pp.57-66
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    • 2010
  • CAS Client personalization means to issue CAS ID or Key for CAS service, which is Core Technology for CAS operation. Protocol A.1 on TTA.KR-07.0079 XCAS, stores CAS Client personalization data from CAS server in XCAS server, and transmits the personalization data by request of XCAS HOST for CAS Client personalization. However, this may increase Network Traffic and CAS Client image management in XCAS server. In this thesis, to complement this, CAS Client personalization is executed on CAS Server by separating CAS service field. Therefore this can distribute Image management and Network Traffic of XCAS server.

A Simulation-Based Development Methodology for CAS (Context-Aware Web Services) Personalization (컨텍스트 기반 맞춤형 웹 서비스 제작을 위한 시뮬레이션 기반 방법론)

  • Chang, Hee-Jung;Kim, Ju-Won;Choi, Sung-Woon;Lee, Kang-Sun
    • Journal of the Korea Society for Simulation
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    • v.15 no.4
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    • pp.11-19
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    • 2006
  • With the emergence of pervasive computing, personalization becomes an important issue to provide with users customized services, anywhere and anytime in their specific environment. Many researches have shown the possibilities of personalization by acquiring and processing sensor information around users. However, personalization remains still at its infancy, since most researches have failed to consider various contexts comprehensively besides sensor data, and just developed tailored services for a specific application domain. In this work, we propose a simulation-based CAS (context Aware Web Services) development methodology. Our methodology considers various contexts on users (eg. current location), web services (eg. response time), devices (eg. availability) and environment (eg. sensor data) all together by simulating them on the fly for personalized and adaptable services.

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