| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | June 3, 2005 |
| Latest Amendment Date: | June 3, 2005 |
| Award Number: | 0509095 |
| Award Instrument: | Standard Grant |
| Program Manager: |
Brett D. Fleisch
CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | June 15, 2005 |
| End Date: | March 31, 2007 (Estimated) |
| Total Intended Award Amount: | $166,882.00 |
| Total Awarded Amount to Date: | $166,882.00 |
| Funds Obligated to Date: |
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| History of Investigator: |
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| Recipient Sponsored Research Office: |
50 COLLEGE ST SOUTH HADLEY MA US 01075-1423 (413)538-2000 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
50 COLLEGE ST SOUTH HADLEY MA US 01075-1423 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): | CSR-Computer Systems Research |
| Primary Program Source: |
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| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
A fundamental challenge for many mobile computing applications is data
management. Data should be available anywhere at anytime. However,
this task is particularly difficult to support with respect to
managing a user's personal data (e.g., data files, email, and cached
web pages) across a collection of personal devices (e.g., a laptop,
PDA, and mobile phone). Two properties of the mobile environment make
data management particularly challenging: network disconnection and
device resource constraints, particularly energy constraints. The
goal of this work is to provide maximal availability and consistency
of personal data as well as maximal aggregate device lifetime for a
collection of personal devices. To accomplish this goal, the project
develops a set of cooperative prefetching algorithms that enable
devices to retrieve relevant data when connected to the information
source. Further, the algorithms efficiently distribute the energy
burden of performing prefetching across the collection of devices.
The evaluation investigates the performance of the algorithms in an
implementation running on a collection of laptop computers and iPAQs.
Two primary metrics are considered: the aggregate lifetime of the
devices and the hit rate of user requests for data. The overarching
impacts of this work will be improved usability of mobile devices and
applications and maximization of mobile device lifetime. Further, the
student participants in this project are undergraduate women from
Mount Holyoke College, one of the nation's finest all-women
undergraduate institutions. Therefore, the project will also serve to
improve the overall participation of women in systems research.
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