A solution of thin-thick client collaboration for data distribution and resource allocation in cloud computing
The International Conference on Information Networking 2014 (ICOIN2014) (2013)
Jan. 28, 2013 to Jan. 30, 2013
Pham Phuoc Hung , Dept. of Comput. Eng., Kyung Hee Univ., Suwon, South Korea
Bui Tuan-Anh , Dept. of Inf. Technol., Hanoi Univ., Hanoi, Vietnam
Eui-Nam Huh , Dept. of Comput. Eng., Kyung Hee Univ., Suwon, South Korea
Recently the massive growth of mobile devices has led to a significant change in the users' computer and Internet usage, along with the dramatic development of mobile services, or mobile computing. Mobile devices, also known as thin clients, limited by either their capacities (CPU, memory or battery) or their network resources, do not always meet users' satisfaction in using mobile services. As a solution to this problem, the thin clients should be connected to other devices with more powerful computing or network resources such as computers and laptops, etc.(thick client), so that the former can capitalize on the latter to strengthen their ability to perform computing tasks. There were a number of related studies in minimizing the limitation of thin client based on the same idea, yet none have been found efficient. In this paper, we present a new method that bases its architecture on the thin-thick client collaboration. We further introduce a strategy to optimize the data distribution, especially big data in cloud computing. Moreover, we propose algorithms to allocate resources to meet service level agreement (SLA) and quality of service (QoS). After a lot of simulations have been conducted and intensively evaluated, the results show that our approach can improve resource allocation efficiency and has better performance than the existing ones.
Resource management, Program processors, Cloud computing, Bandwidth, Computers, Mobile handsets, Quality of service
Pham Phuoc Hung, Bui Tuan-Anh and Eui-Nam Huh, "A solution of thin-thick client collaboration for data distribution and resource allocation in cloud computing," 2013 International Conference on Information Networking (ICOIN), Bangkok, 2013, pp. 238-243.