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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.
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
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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