Abstract
Mobile cloud computing is growing rapidly because its device (i.e., smart phone) is becoming one of the main processing devices for users nowadays. Due to the limitation of resources such as battery life time, CPU and memory capacity, etc., a mobile device cannot satisfy some applications which usually demand more resources than it can afford. To alleviate this, the mobile device should collaborate with external resources to increase its capacity. In order to address these problems, we introduce a collaboration of thin-thick clients which enhances thin client capacities. We further propose a strategy to optimize the data distribution, especially big data in cloud computing. Moreover, we present an algorithm to allocate resources to meet service level agreement (SLA) and conduct simulations to evaluate our approach. Our results evaluation shows that our approach can improve resource allocation efficiency and has better performance than existing approaches.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wikipedia (2012) Mobile phone—Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Mobile_phone. Accessed Sept 2012
Kumar K, Yung-Hsiang L (2010) Cloud computing for mobile users: can offloading computation save energy? IEEE Comput 43(4):51–56
Huerta-Canepa G (2010) A virtual cloud computing provider for mobile devices. In: MCS’10, San Francisco, 15 June 2010
Nguyen T-D (2012) Service image placement for thin client in mobile cloud computing. In: 2012 IEEE. doi:10.1109/CLOUD.2012.39
Plastira Av N (2010) Cloud-based synchronization of distributed file system hierarchies. In: 2010 IEEE
Delgado J, Fong L (2011) Efficiency assessment of parallel workloads on virtualized resources. In: 2011 fourth IEEE international conference
Fan P (2011) Toward optimal deployment of communication-intensive cloud applications. In: Proceedings of international conference on cloud computing
Kwok M (2006) Performance analysis of distributed virtual environments. Ph D Thesis, University of Waterloo, Ontario
Nathan JG (2012) Synchronous parallel processing of big-data analytics services to optimize performance in federated clouds. In: 2012 IEEE, USA
Hu Y (2009) Resource provisioning for cloud computing. In: CASCON ‘09
Li J (2009) Fast scalable optimization to configure service systems having cost and quality of service constraint. In: IEEE 2009
Luo X (2009) From augmented reality to augmented computing: a look at cloud-mobile convergence. In: International symposium on ubiquitous virtual reality
Marinelli E (2009) Hyrax: cloud computing on mobile devices using MapReduce. Master Thesis Draft, Computer Science Department, CMU
Andreolini M (2008) Autonomic request management algorithms for geographically distributed internet-based systems. In: Proceedings of International Conference 2008
Acknowledgments
This research was supported by Next-Generation Information Computing Development Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2012-0006418). The corresponding author is Eui-Nam Huh.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Science+Business Media Dordrecht
About this paper
Cite this paper
Hung, P.P., Huh, EN. (2013). Collaboration of Thin-Thick Clients for Optimizing Data Distribution and Resource Allocation in Cloud Computing. In: Kim, K., Chung, KY. (eds) IT Convergence and Security 2012. Lecture Notes in Electrical Engineering, vol 215. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5860-5_81
Download citation
DOI: https://doi.org/10.1007/978-94-007-5860-5_81
Published:
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5859-9
Online ISBN: 978-94-007-5860-5
eBook Packages: EngineeringEngineering (R0)