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Context-for-wireless: context-sensitive energy-efficient wireless data transfer
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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: Energy efficiency table of contents
Pages: 165 - 178  
Year of Publication: 2007
ISBN:978-1-59593-614-1
Authors
Ahmad Rahmati  Rice University, Houston, TX
Lin Zhong  Rice University, Houston, TX
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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Downloads (6 Weeks): 22,   Downloads (12 Months): 227,   Citation Count: 8
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ABSTRACT

Ubiquitous connectivity on mobile devices will enable numerous new applications in healthcare and multimedia. We set out to check how close we are towards ubiquitous connectivity in our daily life. The findings from our recent field-collected data from an urban university population show that while network availability is decent, the energy cost of network interfaces poses a great challenge. Based on our findings, we propose to leverage the complementary strength of Wi-Fi and cellular networks by choosing wireless interfaces for data transfers based on network condition estimation. We show that an ideal selection policy can more than double the battery lifetime of a commercial mobile phone, and the improvement varies with data transfer patterns and Wi-Fi availability.

We formulate the selection of wireless interfaces as a statistical decision problem. The key to attaining the potential battery improvement is to accurately estimate Wi-Fi network conditions without powering up its network interface. We explore the use of different context information, including time, history, cellular network conditions, and device motion, for this purpose. We consequently devise algorithms that can effectively learn from context information and estimate the probability distribution of Wi-Fi network conditions. Simulations based on field-collected traces show that our algorithms can improve the average battery lifetime of a commercial mobile phone for a three-channel electrocardiogram (ECG) reporting application by 39%, very close to the theoretical upper bound of 42%. Finally, our field validation of our most simple algorithm demonstrates a 35% improvement in battery lifetime.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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CITED BY  10

Collaborative Colleagues:
Ahmad Rahmati: colleagues
Lin Zhong: colleagues