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Abstract: The complexity of developing context-aware pervasive-computing applications calls for distributed software infrastructures that assist applications to collect, aggregate, and disseminate contextual data. In this dissertation, we present a Context Fusion Network (CFN), called Solar, which is built with a scalable and self-organized service overlay. Solar is flexible and allows applications to select distributed data sources and compose them with customized data-fusion operators into a directed acyclic information flow graph. Such a graph represents how an application computes high-level understandings of its execution context from low-level sensory data. To manage application-specified operators on a set of overlay nodes called Planets, Solar provides several unique services such as application-level multicast with policy-driven data reduction to handle buffer overflow, context-sensitive resource discovery to handle environment dynamics, and proactive monitoring and recovery to handle common failures. Experimental results show that these services perform well on a typical DHT-based peer-to-peer routing substrate. In this dissertation, we also discuss experience, insights, and lessons learned from our quantitative analysis of the input sensors, a detailed case study of a Solar application, and development of other applications in different domains.

Note: This is a reformatted version of Guanling Chen's Ph.D. dissertation. Unlike the dissertation submitted to Dartmouth College, this version is single-spaced, uses 11pt fonts, and is formatted specifically for double-sided printing.

Bibliographic citation for this report: [plain text] [BIB] [BibTeX] [Refer]

Or copy and paste:
   Guanling Chen, "Solar: Building A Context Fusion Network for Pervasive Computing." Dartmouth Computer Science Technical Report TR2004-514, August 2004.

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