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Container-Based Cloud Platform for Mobile Computation Offloading

delete2017-05-01
delete35
PRE
AI
S
Song Wu *
C
Chao Niu
J
Jia Rao
金海 (Hai Jin)
X
Xiaohai Dai
DOI:10.1109/IPDPS.2017.47delete
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Abstract

Abstract

En 中文
With the explosive growth of smartphones and cloud computing, mobile cloud, which leverages cloud resource to boost the performance of mobile applications, becomes attractive. Many efforts have been made to improve the performance and reduce energy consumption of mobile devices by offloading computational codes to the cloud. However, the offloading cost caused by the cloud platform has been ignored for many years. In this paper, we propose Rattrap, a lightweight cloud platform which improves the offloading performance from cloud side. To achieve such goals, we analyze the characteristics of typical offloading workloads and design our platform solution accordingly. Rattrap develops a new runtime environment, Cloud Android Container, for mobile computation offloading, replacing heavyweight virtual machines (VMs). Our design exploits the idea of running operating systems with differential kernel features inside containers with driver extensions, which partially breaks the limitation of OS-level virtualization. With proposed resource sharing and code cache mechanism, Rattrap fundamentally improves the offloading performance. Our evaluation shows that Rattrap not only reduces the startup time of runtime environments and shows an average speedup of 16x, but also saves a large amount of system resources such as 75% memory footprint and at least 79% disk capacity. Moreover, Rattrap improves offloading response by as high as 63% over the cloud platform based on VM, and thus saving the battery life.
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Journal

I
IEEE International Parallel and Distributed Processing Symposium
IF:
0
Papers:
8
Citations:
0

Organization

U
university of texas system
Scholars:
18.5W
Papers: 15.6W
Citations: 210