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Dali: a communication-centric data abstraction layer for energy-constrained devices in mobile sensor networks
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International Conference On Mobile Systems, Applications And Services archive
Proceedings of the 5th international conference on Mobile systems, applications and services table of contents
San Juan, Puerto Rico
SESSION: Data access table of contents
Pages: 99 - 112  
Year of Publication: 2007
ISBN:978-1-59593-614-1
Authors
Christopher M. Sadler  Princeton University, Princeton, NJ
Margaret Martonosi  Princeton University, Princeton, NJ
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

Communications in mobile and frequently-disconnected sensor networks are characterized by low-bandwidth radios, unreliable links, and disproportionately high energy costs compared to other system operations. Therefore, we must use as efficiently as possible any periods of connectivity that we have. For this reason, nodes in these networks need mechanisms that organize data to streamline search operations, local computation, and communications.

This work proposes a Data Abstraction Layer (DALi), which is inserted between the application layer and the file system. DALi organizes data with networking in mind to facilitate the development of services for Data Search, Naming, and Reduction that combine to make communications more efficient. From the resulting two-tiered data hierarchy, we develop a multi-layer drill-down search structure that can locate data multiple orders of magnitude faster (and with much lower energy) than simpler data storage structures. Additionally, DALi conserves energy and bandwidth through a mechanism that acknowledges and removes specific data segments from a mobile sensor network. Finally, it seamlessly integrates in a lossless compression algorithm specifically designed for sensor networks to save additional energy.


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Collaborative Colleagues:
Christopher M. Sadler: colleagues
Margaret Martonosi: colleagues