Conference Proceeding Article
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).
Collaborative Sensing, Mobile Phone Sensing, Power Management, Query Optimization
Software and Cyber-Physical Systems
2014 IEEE 15th International Conference on Mobile Data Management: IEEE MDM 2014: 15-18 July 2014, Brisbane, Australia
IEEE Computer Society
City or Country
Los Alamitos, CA
MO, Tianli; SEN, Sougata; LIM, Lipyeow; MISRA, Archan; BALAN, Rajesh Krishna; and LEE, Youngki.
Cloud-based Query Evaluation for Energy-Efficient Mobile Sensing. (2014). 2014 IEEE 15th International Conference on Mobile Data Management: IEEE MDM 2014: 15-18 July 2014, Brisbane, Australia. 221-224. Research Collection School Of Information Systems.
Available at: http://ink.library.smu.edu.sg/sis_research/2661
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