TY - GEN
T1 - Profiling resource usage for mobile applications
T2 - 9th International Conference on Mobile Systems, Applications, and Services, MobiSys'11 and Co-located Workshops
AU - Qian, Feng
AU - Wang, Zhaoguang
AU - Gerber, Alexandre
AU - Mao, Zhuoqing
AU - Sen, Subhabrata
AU - Spatscheck, Oliver
PY - 2011
Y1 - 2011
N2 - Despite the popularity of mobile applications, their performance and energy bottlenecks remain hidden due to a lack of visibility into the resource-constrained mobile execution environment with potentially complex interaction with the application behavior. We design and implement ARO, the mobile Application Resource Optimizer, the first tool that efficiently and accurately exposes the cross-layer interaction among various layers including radio resource channel state, transport layer, application layer, and the user interaction layer to enable the discovery of inefficient resource usage for smartphone applications. To realize this, ARO provides three key novel analyses: (i) accurate inference of lower-layer radio resource control states, (ii) quantification of the resource impact of application traffic patterns, and (iii) detection of energy and radio resource bottlenecks by jointly analyzing cross-layer information. We have implemented ARO and demonstrated its benefit on several essential categories of popular Android applications to detect radio resource and energy inefficiencies, such as unacceptably high (46%) energy overhead of periodic audience measurements and inefficient content prefetching behavior.
AB - Despite the popularity of mobile applications, their performance and energy bottlenecks remain hidden due to a lack of visibility into the resource-constrained mobile execution environment with potentially complex interaction with the application behavior. We design and implement ARO, the mobile Application Resource Optimizer, the first tool that efficiently and accurately exposes the cross-layer interaction among various layers including radio resource channel state, transport layer, application layer, and the user interaction layer to enable the discovery of inefficient resource usage for smartphone applications. To realize this, ARO provides three key novel analyses: (i) accurate inference of lower-layer radio resource control states, (ii) quantification of the resource impact of application traffic patterns, and (iii) detection of energy and radio resource bottlenecks by jointly analyzing cross-layer information. We have implemented ARO and demonstrated its benefit on several essential categories of popular Android applications to detect radio resource and energy inefficiencies, such as unacceptably high (46%) energy overhead of periodic audience measurements and inefficient content prefetching behavior.
KW - 3G networks
KW - UMTS
KW - crosslayer analysis
KW - radio resource optimization
KW - rrc state machine
KW - smartphone applications
UR - http://www.scopus.com/inward/record.url?scp=79961033063&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=79961033063&partnerID=8YFLogxK
U2 - 10.1145/1999995.2000026
DO - 10.1145/1999995.2000026
M3 - Conference contribution
AN - SCOPUS:79961033063
SN - 9781450306430
T3 - MobiSys'11 - Compilation Proceedings of the 9th International Conference on Mobile Systems, Applications and Services and Co-located Workshops
SP - 321
EP - 334
BT - MobiSys'11 - Compilation Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services and Co-located Workshops
Y2 - 28 June 2011 through 1 July 2011
ER -