›› 2017, Vol. 32 ›› Issue (5): 957-973.doi: 10.1007/s11390-017-1775-2

Special Issue: Computer Architecture and Systems

• Computer Networks and Distributed Computing • Previous Articles     Next Articles

Evaluation of Remote-I/O Support for a DSM-Based Computation Offloading Scheme

Yuhun Jun, Jaemin Lee, Euiseong Seo*   

  1. College of Software, Sungkyunkwan University, Suwon 16419, Korea
  • Received:2016-05-30 Revised:2017-03-14 Online:2017-09-05 Published:2017-09-05
  • Contact: Euiseong Seo,euiseong@skku.edu E-mail:euiseong@skku.edu
  • About author:Yuhun Jun received his B.S. degree in electrical and computer engineering from Dankook University, Yong-in, in 2009. He is currently a senior engineer at the Flash Software Development Team in the memory business unit of Samsung Electronics Co., Ltd. His research interests include operating systems, embedded systems, and flash-based storage systems.
  • Supported by:

    This research was supported by the Basic Science Research Program funded by the Ministry of Education of Korea under Grant No. 2015R1D1A1A0057749 and the Research on High Performance and Scalable Manycore OS funded by the MSIP (Ministry of Science and ICT), Korea, under Grant No. B0101-15-0644.

Computation offloading enables mobile devices to execute rich applications by using the abundant computing resources of powerful server systems. The distributed shared memory based (DSM-based) computation offloading approach is expected to be especially popular in the near future because it can dynamically migrate running threads to computing nodes and does not require any modifications of existing applications to do so. The current DSM-based computation offloading scheme, however, has focused on efficiently offloading computationally intensive applications and has not considered the significant performance degradation caused by processing the I/O requests issued by offloaded threads. Because most mobile applications are interactive and thus yield frequent I/O requests, efficient handling of I/O operations is critically important. In this paper, we quantitatively analyze the performance degradation caused by I/O processing in DSM-based computation offloading schemes using representative commodity applications. To remedy the performance degradation, we apply a remote I/O scheme based on remote device support to computation offloading. The proposed approach improves the execution time by up to 43.6% and saves up to 17.7% of energy consumption in comparison with the existing offloading schemes. Selective compression of the remote I/O scheme reduces the network traffic by up to 53.5%.

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