Abstract

Mobile applications are becoming increasingly ubiquitous and provide ever richer functionality on mobile devices. At the same time, such devices often enjoy strong connectivity with more powerful machines ranging from laptops and desktops to commercial clouds. This paper presents the design and implementation of CloneCloud, a system that automatically transforms mobile applications to benefit from the cloud. The system is a flexible application partitioner and execution runtime that enables unmodified mobile applications running in an application-level virtual machine to seamlessly off-load part of their execution from mobile devices onto device clones operating in a computational cloud. CloneCloud uses a combination of static analysis and dynamic profiling to partition applications automatically at a fine granularity while optimizing execution time and energy use for a target computation and communication environment. At runtime, the application partitioning is effected by migrating a thread from the mobile device at a chosen point to the clone in the cloud, executing there for the remainder of the partition, and re-integrating the migrated thread back to the mobile device. Our evaluation shows that CloneCloud can adapt application partitioning to different environments, and can help some applications achieve as much as a 20x execution speed-up and a 20-fold decrease of energy spent on the mobile device.

Keywords

Computer scienceThread (computing)Mobile deviceCloud computingPartition (number theory)Virtual machineEmbedded systemGranularityOperating systemDistributed computingMobile computingRangingComputation

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Publication Info

Year
2011
Type
article
Pages
301-314
Citations
1871
Access
Closed

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Byung-Gon Chun, Sunghwan Ihm, Petros Maniatis et al. (2011). CloneCloud. , 301-314. https://doi.org/10.1145/1966445.1966473

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DOI
10.1145/1966445.1966473