Honolulu, HI, USA USA
June 24, 2012 to June 29, 2012
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CLOUD.2012.48
Mobile devices, such as smart phones and tablets, are becoming the universal interface to online services and applications. However, such devices have limited computational power and battery life, which limits their ability to execute resource-intensive applications. Computation outsourcing to external resources has been proposed as a technique to alleviate this problem. Most existing work on mobile outsourcing has focused on either single application optimization or outsourcing to fixed, local resources, with the assumption that wide-area latency is prohibitively high. However, the opportunity of improving the outsourcing performance by utilizing the relation among multiple applications and optimizing the server provisioning is neglected. In this paper, we present the design and implementation of an Android/Amazon EC2-based mobile application outsourcing framework, leveraging the cloud for scalability, elasticity, and multi-user code/data sharing. Using this framework, we empirically demonstrate that the cloud is not only feasible but desirable as an offloading platform for latency-tolerant applications. We have proposed to use data mining techniques to detect data sharing across multiple applications, and developed novel scheduling algorithms that exploit such data sharing for better outsourcing performance. Additionally, our platform is designed to dynamically scale to support a large number of mobile users concurrently. Experiments show that our proposed techniques and algorithms substantially improve application performance, while achieving high efficiency in terms of computation resource and network usage.
Servers, Outsourcing, Mobile communication, Mobile handsets, Face detection, Performance evaluation, Image processing
Chonglei Mei, Daniel Taylor, Chenyu Wang, Abhishek Chandra, Jon Weissman, "Sharing-Aware Cloud-Based Mobile Outsourcing", CLOUD, 2012, 2013 IEEE Sixth International Conference on Cloud Computing, 2013 IEEE Sixth International Conference on Cloud Computing 2012, pp. 408-415, doi:10.1109/CLOUD.2012.48