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Abstract:
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This dissertation is in the area of pervasive computing .
It focuses on designing platforms for storing , querying , and computing contextual information .
More specifically , we are interested in platforms for storing and querying spatio -temporal events where queries exhibit locality .
Recent advances in sensor technologies have made possible gathering a variety of information on the status of users , the environment machines , etc .
Combining this information with computation we are able to extract context , i .e . , a filtered high -level description of the situation .
In many cases , the information gathered exhibits locality both in space and time , i .e . , an event is likely to be consumed in a location close to the location where the event was produced , at a time whic
h is close to the time the event was produced .
This dissertation builds on this observation to create better platforms for computing context .
We claim three key contributions .
We have studied the problem of designing and optimizing spatial organizations for exchanging context .
Our thesis has original theoretical work on how to create a platform based on cells of a Voronoi diagram for optimizing the energy and bandwidth required for mobiles to exchange contextual information t
hat is tied to specific locations in the platform .
Additionally , we applied our results to the problem of optimizing a system for surveilling the locations of entities within a given region .
We have designed a platform for storing and querying spatio -temporal events exhibiting locality .
Our platform is based on a P2P infrastructure of peers organized based on the Voronoi diagram associated with their locations to store events based on their own associated locations .
We have developed theoretical results based on spatial point processes for the delay experienced by a typical query in this system .
Additionally , we used simulations to study heuristics to improve the performance of our platform .
Finally , we came up with protocols for the replicated storage of events in order to increase the fault -tolerance of our platform .
Finally , in this thesis we propose a design for a platform , based on RFID tags , to support context -aware computing for indoor spaces .
Our platform exploits the structure found in most indoor spaces to encode contextual information in suitably designed RFID tags .
The elements of our platform collaborate based on a set of messages we developed to offer context -aware services to the users of the platform .
We validated our research with an example hardware design of the RFID tag and a software emulation of the tag's functionality . |