TY - GEN
T1 - Exploiting user interest in data-driven cloud-based mobile optimization
AU - Kolb, John
AU - Myott, William
AU - Nguyen, Thao
AU - Chandra, Abhishek
AU - Weissman, Jon
PY - 2014
Y1 - 2014
N2 - In this paper, we present our vision for data-driven cloud-based mobile computing. We identify the concept of Region of interest (RoI) that reflects the profile of the user in how they access information or interact with applications. Such information enables a series of data-driven optimizations: filtering, aggregation, and speculation, that go beyond the well-researched benefit of mobile outsourcing. These optimizations can improve performance, reliability, and energy usage. A novel aspect of our approach is to exploit the unique ability of the cloud to collect and analyze large amounts of user profile data, cache shared data, and even enable sharing of computations, across different mobile users. We implement two exemplar mobile-cloud applications on an Android/Amazon Elastic Cloud Compute (EC2)-based mobile outsourcing platform, that utilize the RoI abstraction for data-driven optimizations. We presentresults driven by workload traces derived from Twitter feeds and Wikipedia document editing to illustrate the opportunities of using such optimizations.
AB - In this paper, we present our vision for data-driven cloud-based mobile computing. We identify the concept of Region of interest (RoI) that reflects the profile of the user in how they access information or interact with applications. Such information enables a series of data-driven optimizations: filtering, aggregation, and speculation, that go beyond the well-researched benefit of mobile outsourcing. These optimizations can improve performance, reliability, and energy usage. A novel aspect of our approach is to exploit the unique ability of the cloud to collect and analyze large amounts of user profile data, cache shared data, and even enable sharing of computations, across different mobile users. We implement two exemplar mobile-cloud applications on an Android/Amazon Elastic Cloud Compute (EC2)-based mobile outsourcing platform, that utilize the RoI abstraction for data-driven optimizations. We presentresults driven by workload traces derived from Twitter feeds and Wikipedia document editing to illustrate the opportunities of using such optimizations.
UR - http://www.scopus.com/inward/record.url?scp=84903832747&partnerID=8YFLogxK
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U2 - 10.1109/MobileCloud.2014.30
DO - 10.1109/MobileCloud.2014.30
M3 - Conference contribution
AN - SCOPUS:84903832747
SN - 9781479925049
T3 - Proceedings - 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2014
SP - 228
EP - 235
BT - Proceedings - 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2014
PB - IEEE Computer Society
T2 - 2nd IEEE International Conference on Mobile Cloud Computing, Services, and Engineering, MobileCloud 2014
Y2 - 7 April 2014 through 10 April 2014
ER -