2nd International ICST Conference on Communications and Networking in China

Research Article

HCAM:A Context-aware Middleware to Support Logic-based Context Conflict Detection

  • @INPROCEEDINGS{10.1109/CHINACOM.2007.4469355,
        author={Ruonan Rao and Guangchang Ye and Jinyuan You},
        title={HCAM:A Context-aware Middleware to Support Logic-based Context Conflict Detection},
        proceedings={2nd International ICST Conference on Communications and Networking in China},
        publisher={IEEE},
        proceedings_a={CHINACOM},
        year={2008},
        month={3},
        keywords={Computer science  Context awareness  Context modeling  Context-aware services  Costs  Engines  Lifting equipment  Logic  Middleware  Page description languages},
        doi={10.1109/CHINACOM.2007.4469355}
    }
    
  • Ruonan Rao
    Guangchang Ye
    Jinyuan You
    Year: 2008
    HCAM:A Context-aware Middleware to Support Logic-based Context Conflict Detection
    CHINACOM
    IEEE
    DOI: 10.1109/CHINACOM.2007.4469355
Ruonan Rao1,*, Guangchang Ye1,*, Jinyuan You1,*
  • 1: Department of Computer Science and Engineering Shanghai Jiao Tong University, Shanghai 200240,China
*Contact email: rao-ruonan@cs.sjtu.edu.cn, ye_gc@sjtu.edu.cn, you-jy@cs.sjtu.edu.cn

Abstract

Context conflict is a key problem since it often occurs in context-aware system when multiple users share the same context at the same time. Context conflict not only causes confusion in applications but also slows down efficiency of context-aware systems. To address these problems, we design a harmonious context-aware middleware (HCAM) and propose a logic-based approach for context conflict detection. Our contextaware middleware provides mechanisms that belong to the middleware layer to simplify development of applications. In our logic-based approach, based on rules representation, we give a classification of context conflict so that we can calculate basic context conflict information from the view of semantics of rules as well as from the view of business logic. Using the inferring axioms, we combine two views together and detect complete context conflict. Experiments show that our logic-based conflict detection approach avoids confusion in applications and reduces unnecessary execution of activated rules to improve efficiency of context-aware middleware.