Takuya Inada, Hiroshi Igaki, Kosuke Ikegami, Shinsuke Matsumoto, Masahide Nakamura, and S. Kusumoto, "Detecting Service Chains and Feature Interactions in Sensor-Driven Home Network Services," Sensors, 12(7), pp. 8447-8464 June 2012.
ID 235
分類 論文誌
タグ chains detecting feature home interactions network sensor-driven service services
表題 (title) Detecting Service Chains and Feature Interactions in Sensor-Driven Home Network Services
表題 (英文)
著者名 (author) Takuya Inada, Hiroshi Igaki, Kosuke Ikegami, Shinsuke Matsumoto, Masahide Nakamura, and Shinji Kusumoto
英文著者名 (author)
キー (key)
定期刊行物名 (journal) Sensors
定期刊行物名 (英文)
巻数 (volume) 12
号数 (number) 7
ページ範囲 (pages) 8447-8464
刊行月 (month) 6
出版年 (year) 2012
Impact Factor (JCR) 1.739
URL http://www.mdpi.com/1424-8220/12/7/8447
付加情報 (note)
注釈 (annote)
内容梗概 (abstract) Sensor-driven services often cause chain reactions, since one service may generate an environmental impact that automatically triggers another service. We first propose a framework that can formalize and detect such service chains based on ECA (event, condition, action) rules. Although the service chain can be a major source of feature interactions, not all service chains lead to harmful interactions. Therefore, we then propose a method that identifies feature interactions within the service chains. Specifically, we characterize the degree of deviation of every service chain by evaluating the gap between expected and actual service states. An experimental evaluation demonstrates that the proposed method successfully detects 11 service chains and 6 feature interactions within 7 practical sensor-driven services.
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BiBTeXエントリ
@article{id235,
         title = {Detecting Service Chains and Feature Interactions in Sensor-Driven Home Network Services},
        author = {Takuya Inada, Hiroshi Igaki, Kosuke Ikegami, Shinsuke Matsumoto, Masahide Nakamura, and Shinji Kusumoto},
       journal = {Sensors},
        volume = {12},
        number = {7},
         pages = {8447-8464},
         month = {6},
          year = {2012},
    impactfactor = {1.739},
}