Publication Type

Conference Proceeding Article

Publication Date

7-2014

Abstract

In this paper, we reduce the energy overheads of continuous mobile sensing for context-aware applications that are interested in collective context or events. We propose a cloud-based query management and optimization framework, called CloQue, which can support concurrent queries, executing over thousands of individual smartphones. CloQue exploits correlation across context of different users to reduce energy overheads via two key innovations: i) Dynamically reordering the order of predicate processing to preferentially select predicates with not just lower sensing cost and higher selectivity, but that maximally reduce the uncertainty about other context predicates, and ii) intelligently propagating the query evaluation results to dynamically update the uncertainty of other correlated, but yet-to-be evaluated, context predicates. An evaluation, using real cell phone traces from a real world dataset shows significant energy savings (between 30 to 50% compared with traditional short-circuit systems) with little loss in accuracy (5% at most).

Keywords

Collaborative Sensing, Mobile Phone Sensing, Power Management, Query Optimization

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

2014 IEEE 15th International Conference on Mobile Data Management: IEEE MDM 2014: 15-18 July 2014, Brisbane, Australia

First Page

221

Last Page

224

ISBN

9781479957064

Identifier

10.1109/MDM.2014.33

Publisher

IEEE Computer Society

City or Country

Los Alamitos, CA

Copyright Owner and License

Authors

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1109/MDM.2014.33

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