Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2013

Abstract

Many emerging context-aware mobile applications involve the execution of continuous queries over sensor data streams generated by a variety of on-board sensors on multiple personal mobile devices (aka smartphones). To reduce the energyoverheads of such large-scale, continuous mobile sensing and query processing, this paper introduces CQP, a collaborative query processing framework that exploits the overlap (in both the sensor sources and the query predicates) across multiple smartphones. The framework automatically identifies the shareable parts of multiple executing queries, and then reduces the overheads of repetitive execution and data transmissions, by having a set of 'leader' mobile nodes execute and disseminate these shareable partial results. To further reduce energy, CQP utilizes lower-energy short-range wireless links (such as Bluetooth) to disseminate such results directly among proximate smartphones. We describe algorithms to support our server-assisted distributed query sharing and optimization strategy. Simulation experiments indicate that this approach can result in 60% reduction in the energy overhead of continuous query processing, when 'leader' selection is dynamically rotated to equitably share the burden, we observe an increase of up to 65% in operational lifetime.

Keywords

Collaboration, Mobile communication, Query processing, Sensors, Servers, Smart phones

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

2013 IEEE 14th International Conference on Mobile Data Management: 3-6 June 2013, Milan, Italy: Proceedings

First Page

147

Last Page

156

ISBN

9781467360685

Identifier

10.1109/MDM.2013.25

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1109/MDM.2013.25

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