Abstract
With the increasing demands for adaptive middleware of real-time embedded systems in ubiquitous computing environments, the need for novel software architecture and programming infrastructure to manage data is widely recognized. In this paper, we present SAM (Semantic and Adaptive Middleware), an efficient middleware architecture that supports for real-time embedded system in smart vehicle space. The SAM’s architecture is based on embedded real-time OS and CAN-based communication environment, which includes tinyORB kernel, distributed components, distributed meta objects, services and tools. In SAM, we mainly utilize context-sensitive repository and knowledge management technology to realize adaptive characteristic. The two contributions of this paper are the proposal of SVA (Semantic Virtual Agent) and component-level adaptive mechanism. The SVAs use SIP (Semantic Interface Protocol) to communicate and auto-update themselves. To achieve self-adaptation and reflection of component-level, the component hook mechanism is introduced. In addition, we have brought into further discussion of the hardware infrastructure and one application of SAM to manage heterogeneous data.
This research was supported by 863 National High Technology Program under Grant No. 2003AA1Z2080, “Research of Operating System to Support Ubiquitous Computing”
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Wu, Q., Wu, Z., Wu, B., Jiang, Z. (2004). Semantic and Adaptive Middleware for Data Management in Smart Vehicle Space. In: Li, Q., Wang, G., Feng, L. (eds) Advances in Web-Age Information Management. WAIM 2004. Lecture Notes in Computer Science, vol 3129. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27772-9_12
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DOI: https://doi.org/10.1007/978-3-540-27772-9_12
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