TY - GEN
T1 - Exhausting battery statistics
T2 - 2010 ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds, MobiHeld '10, Co-located with SIGCOMM 2010
AU - Vallina-Rodriguez, Narseo
AU - Hui, Pan
AU - Crowcroft, Jon
AU - Rice, Andrew
PY - 2010
Y1 - 2010
N2 - Despite the advances in battery technologies, mobile phones still suffer from severe energy limitations. Modern handsets are rich devices that can support multitasking thanks to their high processing power and provide a wide range of resources such as sensors and network interfaces with different energy demands. There have been multiple attempts to characterise those energy demands; both to save or to allocate energy to the applications on the handset. However, there is still little understanding on how the interdependencies between resources (interdependencies caused by the applications and users' behaviour) affect the battery life. In this paper, we demonstrate the necessity of considering all those dynamics in order to characterise the energy demands of the system accurately. These results indicate that simple algorithmic and rule-based scheduling techniques [7] are not the most appropriate way of managing the resources since their usage can be affected by contextual factors, making necessary to find customised solutions that consider each user's behaviour and handset features.
AB - Despite the advances in battery technologies, mobile phones still suffer from severe energy limitations. Modern handsets are rich devices that can support multitasking thanks to their high processing power and provide a wide range of resources such as sensors and network interfaces with different energy demands. There have been multiple attempts to characterise those energy demands; both to save or to allocate energy to the applications on the handset. However, there is still little understanding on how the interdependencies between resources (interdependencies caused by the applications and users' behaviour) affect the battery life. In this paper, we demonstrate the necessity of considering all those dynamics in order to characterise the energy demands of the system accurately. These results indicate that simple algorithmic and rule-based scheduling techniques [7] are not the most appropriate way of managing the resources since their usage can be affected by contextual factors, making necessary to find customised solutions that consider each user's behaviour and handset features.
KW - resources demand
KW - smartphone usage
KW - user behaviour
UR - http://www.scopus.com/inward/record.url?scp=78149320954&partnerID=8YFLogxK
U2 - 10.1145/1851322.1851327
DO - 10.1145/1851322.1851327
M3 - Conference Paper published in a book
AN - SCOPUS:78149320954
SN - 9781450301978
T3 - Proceedings of the 2nd ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds, MobiHeld '10, Co-located with SIGCOMM 2010
SP - 9
EP - 14
BT - Proceedings of the 2nd ACM SIGCOMM Workshop on Networking, Systems, and Applications on Mobile Handhelds, MobiHeld '10, Co-located with SIGCOMM 2010
Y2 - 30 August 2010 through 30 August 2010
ER -