ProxStor is a cloud-based human proximity storage and query informational system taking advantage of both the near ubiquity of mobile devices and the growing digital infrastructure in our everyday physical world, commonly referred to as the Internet of Things (IoT). The combination provides the opportunity for mobile devices to identify when entering and leaving the proximity of a space based upon this unique identifying infrastructure information. ProxStor provides a low-overhead interface for storing these proximity events while additionally offering search and query capabilities to enable a richer class of location aware applications. ProxStor scales up to store and manage more than one billion objects, while enabling future horizontal scaling to expand to multiple systems working together supporting even more objects. A single seamless web interface is presented to clients system.. More than 18 popular graph database systems are supported behind ProxStor. Performance benchmarks while running on Neo4j and OrientDB graph database systems are compared to determine feasibility of the design. / text
| Identifer | oai:union.ndltd.org:UTEXAS/oai:repositories.lib.utexas.edu:2152/28536 |
| Date | 17 February 2015 |
| Creators | Giannoules, James Peter |
| Source Sets | University of Texas |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | application/pdf |
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