Peer-to-Peer Networking and Applications

, Volume 11, Issue 4, pp 711–722 | Cite as

A block-level caching optimization method for mobile transparent computing

  • Yayuan Tang
  • Kehua Guo
  • Biao Tian
Part of the following topical collections:
  1. Special Issue on Transparent Computing


In mobile transparent computing, a large number of concurrent data requests from heterogeneous clients via the network need to be processed in a timely fashion, and servers have to repeatedly fetch (search and read) the data from storage, which may cause numerous I/O costs. Generally, disk access speed is more limited than memory; therefore, massive I/O operations at servers may become a bottleneck for the system, and transport delay of the total network caused by the limitation of wireless bandwidth and stability may lead to poorer user experience. Hence, caching method plays a significant role in performance improvement of transparent computing systems. In this paper, we propose a block-level caching optimization method for the server and client by analyzing the system bottleneck in mobile transparent computing. We first analyze the storage format of the data file and the three-layer structure in the server according to the characteristics of requesting data from the client to the server and propose a block-level cache based on the access time and access frequency for the server. Second, considering the restriction of bandwidth and stability of the wireless network, we analyze network boot processes from the client’s startup and propose a client block-level cache optimization combined with local storage access technology. Finally, experimental results demonstrate that the server block-level cache optimization can effectively reduce the amount of server disk I/O, improving the concurrent ability of the server. In addition, the client block-level cache can significantly increase startup speed of the client, reduce network traffic and improve user experience.


I/O request Block-level cache Caching algorithm Mobile transparent computing 



This work is supported by the Major Science and Technology Research Program for Strategic Emerging Industry of Hunan (2012GK4106), International Science and Technology Cooperation Special Projects of China (2013DFB10070), Hunan Science and Technology Plan (2012RS4054), Natural Science Foundation of China (61672535, 61472005, 61561027), Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Innovation Fund (JYB201502), Natural Science Foundation of Shanghai (16ZR1415100), Project of Innovation-driven Plan in Central South University (2015CXS010), Key Laboratory of Information Processing and Intelligent Control of Fujian Innovation Fund (MJUKF201735), and Graduate Student Research Innovation Project of Hunan Province (CX2016B049). The authors declare that they have no conflict of interests.


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.School of Information Science and EngineeringCentral South UniversityChangshaChina
  2. 2.School of Electronics and Information EngineeringHunan University of Science and EngineeringYongzhouChina
  3. 3.Key Laboratory of Information Processing and Intelligent Control of FujianMinjiang UniversityFuzhouChina

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