Grant: Strategic Projects - Group
University of Waterloo
$139,875.00
Optimal data structures for organization and retrieval of spatial data
FY 2008-09
Summary
This research will investigate optimal approaches for the storage, retrieval and dynamic updating spatial data in a distributed networked environment. Spatial data are commonly used to describe, among other applications, geographic and geospatial information. This research will investigate how to optimally organize, distribute and replicate data as to support efficient searchability and as a consequence enhance data availability. There is a strong need for this research. Large stores of spatial data now exist, including satellite (e.g. RADARSAT) imagery, geographical mapping, aerial video inspection and weather observations, with new spatial data continually being gathered. Indeed, recent advances in sensor technology have led to an increase of several orders of magnitude in the amount of data collected. These large collections can only be hosted in a distributed manner across several hosts in a networked environment, either locally or remotely. This brings a host of research questions that need to be addressed, chiefly: - The design of spatial data structures and algorithms for geographic information systems that have as low a memory footprint as possible and still allow operations such as node additions and removals, node locking, range queries to be performed efficiently. - I/O aware spatial data structures that are sensitive to varying access costs across the memory hierarchy, including issues related to the cost of distributed, remote and secondary storage. - Caching strategies for distributed spatial data structures that to coordinate paging of indexing structures in order to reduce external (network or disk) accesses given changes in user requests. - Issues of consistency, replication and recoverability in distributed massive spatial data structures. - Data management and organization of geo-spatial data in ways that maintain efficiency of access, accuracy of data, as well as the ability to distribute the data. - Design of data structures for storing massive amounts of data that can be readily distributed over a network.
Program
Strategic Projects - Group
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
350623-2007
Name nom
LopezOrtiz, Alejandro
Department département
Computer Science, School of
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2008
Competition year année de concours
2007
Award amount
139875
Program id
STPGP
Program nane en
Strategic Projects - Group
Program name fr
Projets stratégiques - De groupe
Group en
Research partnerships programs
Group fr
Programmes de partenariat
Committee code
1041
Committee name en
Strategic Projects Selection Panel - Communications and Information
Committee name fr
Comité de sélection des projets stratégiques - Communication et information
Area of application code
1207
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Information, computer and communication technologies
Area of application fr
Technologie de l'information, des ordinateurs et des réseaux de communications
Research subject code
2713
Research subject group en
Information technology
Research subject group fr
Technologie de l'information
Research subject en
Algorithms
Research subject fr
Algorithmes
Partie
2
Nb partie
3
Application title
Optimal data structures for organization and retrieval of spatial data
Keyword
NA
Application summary
This research will investigate optimal approaches for the storage, retrieval and dynamic updating spatial data in a distributed networked environment. Spatial data are commonly used to describe, among other applications, geographic and geospatial information. This research will investigate how to optimally organize, distribute and replicate data as to support efficient searchability and as a consequence enhance data availability. There is a strong need for this research. Large stores of spatial data now exist, including satellite (e.g. RADARSAT) imagery, geographical mapping, aerial video inspection and weather observations, with new spatial data continually being gathered. Indeed, recent advances in sensor technology have led to an increase of several orders of magnitude in the amount of data collected. These large collections can only be hosted in a distributed manner across several hosts in a networked environment, either locally or remotely. This brings a host of research questions that need to be addressed, chiefly: - The design of spatial data structures and algorithms for geographic information systems that have as low a memory footprint as possible and still allow operations such as node additions and removals, node locking, range queries to be performed efficiently. - I/O aware spatial data structures that are sensitive to varying access costs across the memory hierarchy, including issues related to the cost of distributed, remote and secondary storage. - Caching strategies for distributed spatial data structures that to coordinate paging of indexing structures in order to reduce external (network or disk) accesses given changes in user requests. - Issues of consistency, replication and recoverability in distributed massive spatial data structures. - Data management and organization of geo-spatial data in ways that maintain efficiency of access, accuracy of data, as well as the ability to distribute the data. - Design of data structures for storing massive amounts of data that can be readily distributed over a network.