Optimal collaboration of thin---thick clients and resource allocation in cloud computing

  • Authors:

  • Pham Phuoc Hung;Tuan-Anh Bui;Mauricio Alejandro Morales;Mui Nguyen;Eui-Nam Huh

  • Affiliations:

  • Department of Computer Engineering, Kyung Hee University, Suwon, South Korea;Department of Information Technology, Hanoi University, Hanoi, Vietnam;Department of Computer Engineering, Kyung Hee University, Suwon, South Korea;Department of Computer Engineering, Kyung Hee University, Suwon, South Korea;Department of Computer Engineering, Kyung Hee University, Suwon, South Korea

  • Venue:
  • Personal and Ubiquitous Computing
  • Year:
  • 2014

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Abstract

Cloud computing (CC) has recently become a rising paradigm in the information and communications technology industry, drawing a lot of attentions to professionals and researchers. During the last decade, the dominance of smart phones or tablet computers (known as thin clients) over traditional desktop or laptop computers (known as thick clients) has become more and more evident, reflecting a great change in the way people access the Internet. Despite the recent technology advancements that manufacture a new generation of mobile devices with generous resources, the fact that they can offer only limited processing capacity still remains a painful experience. This problem, fortunately, has been made less severe thanks to the recent adoption of CC platform. CC enables offloading heavy processing tasks up to the "cloud", leaving only simple jobs to the user-end capacity-limited thin clients. So far, a number of research studies have been carried out, trying to eliminate problems arising from shortcomings in the connection between thin clients and cloud networks, yet little have been found efficient. In this paper, we present a novel architecture, taking advantage of collaboration of thin and thick clients, particularly aiming at optimizing data distribution and utilizing CC resources so that expected Quality-of-Service requirements can be met. We also propose an algorithm to select an optimal resource allocation strategy to satisfy various Service Level Agreements. In order to justify our proposal, we have used both numerical analysis and programming approaches. Simulation result shows that our proposed schemes can improve resource allocation efficiency and achieve better performance than the existing ones.