An opportunistic platform for Android-based mobile devices
MobiOpp '10 Proceedings of the Second International Workshop on Mobile Opportunistic Networking
MAUI: making smartphones last longer with code offload
Proceedings of the 8th international conference on Mobile systems, applications, and services
Anatomizing application performance differences on smartphones
Proceedings of the 8th international conference on Mobile systems, applications, and services
Proceedings of the 8th international conference on Mobile systems, applications, and services
An analysis of power consumption in a smartphone
USENIXATC'10 Proceedings of the 2010 USENIX conference on USENIX annual technical conference
TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones
OSDI'10 Proceedings of the 9th USENIX conference on Operating systems design and implementation
Keypad: an auditing file system for theft-prone devices
Proceedings of the sixth conference on Computer systems
Fine-grained power modeling for smartphones using system call tracing
Proceedings of the sixth conference on Computer systems
CloneCloud: elastic execution between mobile device and cloud
Proceedings of the sixth conference on Computer systems
Security versus energy tradeoffs in host-based mobile malware detection
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Why are web browsers slow on smartphones?
Proceedings of the 12th Workshop on Mobile Computing Systems and Applications
Storage-aware smartphone energy savings
Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing
ASCDS: a smartphone confidential data storage scheme
International Journal of Wireless and Mobile Computing
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Conventional wisdom holds that storage is not a big contributor to application performance or energy consumption on mobile devices. Flash storage (the type most commonly used today) draws little power, and its performance is thought to exceed that of the network subsystem. In this paper we present initial evidence to the contrary even for common applications such as web browsing or application install. We find that just by varying the underlying flash storage, performance of web browsing over WiFi can vary roughly by 500%, and of application install by 300%. With a faster network (setup over USB), storage is taxed even more and the performance variation rose to roughly 700% for web browsing! The performance variation can be attributed to the characteristics of the storage device, the workload pattern (random or sequential), and the operating system itself. We also find that lower storage performance leads to increased CPU consumption, thus having an indirect impact on energy.