Computer Science – Distributed – Parallel – and Cluster Computing
Scientific paper
2010-09-16
Computer Science
Distributed, Parallel, and Cluster Computing
Scientific paper
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 optimally and automatically partition an application so that it migrates, executes in the cloud, and re-integrates computation in a fine-grained manner that makes efficient use of resources. Our evaluation shows that CloneCloud can achieve up to 21.2x speedup of smartphone applications we tested and it allows different partitioning for different inputs and networks.
Chun Byung-Gon
Ihm Sunghwan
Maniatis Petros
Naik Mayur
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