Adaptive Computation Offloading from Mobile Devices into the Cloud

The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote clo...

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Bibliographic Details
Published in:2012 IEEE 10th International Symposium on Parallel and Distributed Processing with Applications pp. 784 - 791
Main Authors: Kovachev, D., Tian Yu, Klamma, R.
Format: Conference Proceeding
Language:English
Published: IEEE 01.07.2012
Subjects:
Androids
cloud computing
Computational modeling
Hardware
Middleware
Mobile communication
mobile computing
Smart phones
ISBN:1467316318, 9781467316316
ISSN:2158-9178
Online Access:Get full text
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Summary:The inherently limited processing power and battery lifetime of mobile phones hinder the possible execution of computationally intensive applications like content-based video analysis or 3D modeling. Offloading of computationally intensive application parts from the mobile platform into a remote cloud infrastructure or nearby idle computers addresses this problem. This paper presents our Mobile Augmentation Cloud Services (MACS) middleware which enables adaptive extension of Android application execution from a mobile client into the cloud. Applications are developed by using the standard Android development pattern. The middleware does the heavy lifting of adaptive application partitioning, resource monitoring and computation offloading. These elastic mobile applications can run as usual mobile application, but they can also reach transparently remote computing resources. Two prototype applications using the MACS middleware demonstrate the benefits of the approach. The evaluation shows that applications, which involve complicated algorithms and large computations, can benefit from offloading with around 95% energy savings and significant performance gains compared to local execution only.
ISBN:1467316318
9781467316316
ISSN:2158-9178
DOI:10.1109/ISPA.2012.115