| dc.contributor.advisor |
De Veciana , Gustavo |
|
| dc.contributor.committeeMember |
Garg , Vijay |
|
| dc.contributor.committeeMember |
Mok , Al |
|
| dc.contributor.committeeMember |
Julien , Christine |
|
| dc.contributor.committeeMember |
Touba , Nur |
|
| dc.contributor.committeeMember |
Breternitz , Mauricio |
|
| dc.creator |
Ziotopoulos , Agisilaos Georgios |
|
| dc.date.accessioned |
2011 -06 -02T14 :25 :16Z |
|
| dc.date.accessioned |
2011 -06 -02T14 :25 :35Z |
|
| dc.date.accessioned |
2011 -08 -17T14 :35 :33Z |
|
| dc.date.available |
2011 -06 -02T14 :25 :16Z |
|
| dc.date.available |
2011 -06 -02T14 :25 :35Z |
|
| dc.date.available |
2011 -08 -17T14 :35 :33Z |
|
| dc.date.created |
2011 -05 |
|
| dc.date.issued |
2011 -06 -02 |
|
| dc.date.submitted |
May 2011 |
|
| dc.identifier.uri |
http : / /hdl .handle .net /2152 /ETD -UT -2011 -05 -3328 |
|
| dc.description.abstract |
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 . |
|
| dc.format.mimetype |
application /pdf |
|
| dc.language.iso |
eng |
|
| dc.subject |
Stochastic geometry |
|
| dc.subject |
Pervasive computing |
|
| dc.subject |
Computer architecture |
|
| dc.subject |
Spatial data |
|
| dc.subject |
Spatio -temporal data |
|
| dc.subject |
P2P networks |
|
| dc.title |
Design of platforms for computing context with spatio -temporal locality |
|
| dc.description.department |
Electrical and Computer Engineering |
|
| dc.type.genre |
thesis |
* |
| dc.type.material |
text |
* |
| thesis.degree.name |
Doctor of Philosophy |
|
| thesis.degree.level |
Doctoral |
|
| thesis.degree.discipline |
Electrical and Computer Engineering |
|
| thesis.degree.grantor |
University of Texas at Austin |
|
| thesis.degree.department |
Electrical and Computer Engineering |
|
| dc.date.updated |
2011 -06 -02T14 :25 :35Z |
|