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

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Abstract

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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References

  1. Fernando N, Loke S W, Rahayu W. Mobile cloud computing: A survey. Future Generation Computing Systems, 2013, 29(1): 84–106.

    Article  Google Scholar 

  2. Satyanarayanan M, Bahl P, Caceres R, Davies N. The case for VM-based cloudlets in mobile computing. IEEE Pervasive Computing, 2009, 8(4): 14–23.

    Article  Google Scholar 

  3. Chun B G, Ihm S, Maniatis P, Naik M, Patti A. CloneCloud: Elastic execution between mobile device and cloud. In Proc. the 6th ACM European Conference on Computer Systems, Apr. 2011, pp.301-314.

  4. Gordon M S, Jamshidi D A, Mahlke S, Mao Z M, Chen X. COMET: Code offload by migrating execution transparently. In Proc. the 10th USENIX Conference on Operating Systems Design and Implementation (OSDI), Oct. 2012, pp.93-106.

  5. Seo B K, Maeng S, Lee J, Seo E. DRACO: A deduplicating FTL that provides tangible extra capacity. IEEE Computer Architecture Letters, 2015, 14(2): 123–126.

    Article  Google Scholar 

  6. Kemp R, Palmer N, Kielmann T, Bal H E. Cuckoo: A computation offloading framework for smartphones. In Proc. the 2nd International ICST Conference on Mobile Computing, Applications, and Services, Oct. 2010.

  7. Kovachev D, Yu T, Klamma R. Adaptive computation offloading from mobile devices into the cloud. In Proc. the 10th IEEE International Symposium on Parallel and Distributed Processing with Applications (ISPA), July 2012, pp.784-791.

  8. Cuervo E, Balasubramanian A, Cho D k, Wolman A, Saroiu S, Chandra R, Bahl P. MAUI: Making smartphones last longer with code offload. In Proc. the 8th International Conference on Mobile Systems, Applications, and Services (MobiSys), June 2010, pp.49-62.

  9. Li Z, Wang C, Xu R. Computation offloading to save energy on handheld devices: A partition scheme. In Proc. the International Conference on Compilers, Architecture, and Synthesis for Embedded Systems, Nov. 2001, pp.238-246.

  10. Messer A, Greenberg I, Bernadat P, Milojicic D, Chen D, Giuli T, Gu X. Towards a distributed platform for resourceconstrained devices. In Proc. the 22nd International Conference on Distributed Computing Systems (ICDCS), July 2002, pp.43-51.

  11. Zhou Y, Iftode L, Li K. Performance evaluation of two home-based lazy release consistency protocols for shared virtual memory systems. ACM SIGOPS Operating Systems Review, 1996, 30(SI): 75–88.

  12. Bradski G. The openCV library. Doctor Dobbs Journal, 2000, 25(11): 120–126.

    Google Scholar 

  13. Ko M. Technical overview of iSCSI extensions for RDMA (iSER) & Datamover architecture for iSCSI (DA). http://www.rdmaconsortium.org/home/iSER DA intro.pdf, Mar. 2017.

  14. Liu J, Panda D K, Banikazemi M. Evaluating the impact of RDMA on storage I/O over Infiniband. In Proc. HPCA-10, Feb. 2004.

  15. Thiagarajan A, Ravindranath L, LaCurts K, Madden S, Balakrishnan H, Toledo S, Eriksson J. VTrack: Accurate, energy-aware road traffic delay estimation using mobile phones. In Proc. the 7th ACM Conference on Embedded Networked Sensor Systems, Nov. 2009, pp.85-98.

  16. Lee Y, Ju Y, Min C, Kang S, Hwang I, Song J. CoMon: Cooperative ambience monitoring platform with continuity and benefit awareness. In Proc. the 10th International Conference on Mobile systems, Applications, and Services, June 2012, pp.43-56.

  17. Cornelius C, Kapadia A, Kotz D, Peebles D, Shin M, Triandopoulos N. Anonysense: Privacy-aware people-centric sensing. In Proc. the 6th International Conference on Mobile Systems, Applications, and Services, June 2008, pp.211-224.

  18. Das T, Mohan P, Padmanabhan V N, Ramjee R, Sharma A. PRISM: Platform for remote sensing using smartphones. In Proc. the 8th International Conference on Mobile Systems, Applications, and Services, June 2010, pp.63-76.

  19. Amiri Sani A, Boos K, Yun M H, Zhong L. Rio: A system solution for sharing I/O between mobile systems. In Proc. the 12th Annual International Conference on Mobile Systems, Applications, and Services, June 2014, pp.259-272.

  20. Barham P, Dragovic B, Fraser K, Hand S, Harris T, Ho A, Neugebauer R, Pratt I, Warfield A. Xen and the art of virtualization. In Proc. the 19th ACM Symposium on Operating Systems Principles, Oct. 2003, pp.164-177.

  21. Sani A A, Boos K, Qin S, Zhong L. I/O paravirtualization at the device file boundary. In Proc. the 19th International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS), Mar. 2014, pp.319-332.

  22. Oberhumer M. LZO real-time data compression library. User manual for LZO version 0.28. http://sourceforge. net/projects/1201, Aug. 2017.

  23. Barr K C, Asanović K. Energy-aware lossless data compression. ACM Transactions on Computer Systems (TOCS), 2006, 24(3): 250–291.

    Article  Google Scholar 

  24. Xu R, Li Z, Wang C, Ni P. Impact of data compression on energy consumption of wireless-networked handheld devices. In Proc. the 23rd Int. Conf. Distributed Computing Systems, May 2003, pp.302-311.

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Correspondence to Euiseong Seo.

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Jun, Y., Lee, J. & Seo, E. Evaluation of Remote-I/O Support for a DSM-Based Computation Offloading Scheme. J. Comput. Sci. Technol. 32, 957–973 (2017). https://doi.org/10.1007/s11390-017-1775-2

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  • DOI: https://doi.org/10.1007/s11390-017-1775-2

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