Cloud-based Query Evaluation for Energy-Efficient Mobile Sensing
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 tho...
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| Main Authors: | , , , , , |
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| Format: | text |
| Language: | English |
| Published: |
Institutional Knowledge at Singapore Management University
2014
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| Subjects: | |
| Online Access: | https://ink.library.smu.edu.sg/sis_research/2661 https://ink.library.smu.edu.sg/context/sis_research/article/3661/viewcontent/mdm14_cloud.pdf |
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| Institution: | Singapore Management University |
| Language: | English |
| Summary: | 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). |
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