Abstract
In this paper, we propose a mathematical mobile cloud computing system called M2C. This cloud system allows users to execute MATLAB instructions on their Android-based mobile devices, and take advantage of diverse resources including CPUs and GPUs available in clouds to speed up the execution of their MATLAB applications. On the other hand, M2C supports time sharing on license codes to reduce the waiting time of users, and optimizes resource configurations for maximizing the performance of user applications, and automatically recover system services from faults. Consequently, M2C provides a reliable and efficient service for mobile users to perform data-intensive mathematic computation anytime and anywhere.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
MathWorks, MATLAB – The language of technical computing, http://www.mathworks.com/products/matlab
Google Project Hosting, addi–Matlab/Octave clone for Android, https://code.google.com/p/addi
Eaton, J.W.: GUN Octave, http://www.gnu.org/software/octave/index.html
MathWork, Parallel Computing Toolbox, http://www.mathworks.com/products/parallel-computing/?s_cid=sol_compbio_sub2_relprod4_parallel_computing_toolbox
Owens, J.D., Luebke, D., Govindaraju, N., Harris, M., Krüger, J., Lefohn, A.E., Purcell, T.J.: A Survey of General-Purpose Computation on Graphics Hardware. Computer Graphics Forum, 80–113 (2007)
Chine, K.: Learning math and statistics on the cloud, towards an EC2-based Google Docs-like portal for teaching/learning collaboratively with R and Scilab. In: 10th IEEE International Conference on Advanced Learning Technologies, pp. 752–753 (2010)
Gallagher, P.D.: The NIST definition of cloud computing. National Institute of Standards and Technology, http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf
Amazon, Amazon Elastic Compute Cloud, https://aws.amazon.com/ec2/
AccelerEyes, ArrayFire software library, http://www.accelereyes.com
Liang, T.-Y., Wu, J.-K., Chen, Y.-C.: An Acceleration Toolkit of MATLAB based on Hybrid CPU/GPU Clusters. In: Proceedings of IEEE 16th Conference on Computer Science and Engineering, pp. 50–57 (2013)
AMD Group, Core Math Library (ACML), http://developer.amd.com/tools/cpu-development/amd-core-math-library-acml
NVIDIA, CUDA toolkit document, http://docs.nvidia.com/cuda/cublas/index.htm
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this paper
Cite this paper
Liang, TY., Li, YJ., He, GJ., Liao, JC. (2014). A Mathematic Mobile Cloud Computing System. In: Hsu, R.CH., Wang, S. (eds) Internet of Vehicles – Technologies and Services. IOV 2014. Lecture Notes in Computer Science, vol 8662. Springer, Cham. https://doi.org/10.1007/978-3-319-11167-4_28
Download citation
DOI: https://doi.org/10.1007/978-3-319-11167-4_28
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11166-7
Online ISBN: 978-3-319-11167-4
eBook Packages: Computer ScienceComputer Science (R0)