[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.5555/3330299.3330334acmconferencesArticle/Chapter ViewAbstractPublication Pagesds-rtConference Proceedingsconference-collections
research-article

SEECSSim: a parallel and distributed simulation framework for mobile devices

Published: 15 October 2018 Publication History

Abstract

On battery-operated devices, energy and power consumption are main concerns. With the recent advancement of technology, mobile devices can be integrated with traditional systems for running complex computations. In fact, mobile devices can easily become part of computational networks and share their computational and memory resources. Despite this, traditional simulation frameworks are not designed to perform well on heterogeneous networks. This is mainly due to the limited computational resources that are available on mobile devices. In this paper, we propose SEECSSim (SEECSSim is derived from School of Electrical Engineering and Computer Science (SEECS)) that is a simulation framework specifically designed for mobile devices. SEECSSim includes state-of-the-art distributed synchronization algorithms that are implemented to run on mobile or embedded devices. To benchmark the proposed framework, the well-known PHOLD model is used and performance results are reported in terms of execution time, CPU usage, memory and energy consumption.

References

[1]
R. M. Fujimoto, R. Bagrodia, R. E. Bryant, K. M. Chandy, D. Jefferson, J. Misra, D. Nicol, and B. Unger, "Paralle discrete event simulation: The making of a field," 2017.
[2]
R. M. Fujimoto, Parallel and distributed simulation systems. Wiley New York, 2000, vol. 300.
[3]
A. W. Malik, A. J. Park, and R. M. Fujimoto, "An optimistic parallel simulation protocol for cloud computing environments," SCS M&S Magazine, vol. 4, pp. 1--9, 2010.
[4]
K. Vanmechelen, S. De Munck, and J. Broeckhove, "Conservative distributed discrete event simulation on amazon ec2," in Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012). IEEE Computer Society, 2012, pp. 853--860.
[5]
Y. Wu, J. Cao, and M. Li, "Private cloud system based on boinc with support for parallel and distributed simulation," in Dependable, Autonomic and Secure Computing (DASC), 2011 IEEE Ninth International Conference on. IEEE, 2011, pp. 1172--1178.
[6]
O. S. Unsal and C. M. Krishna, "System-levelpower-aware computing in complex real-time and multimedia systems," Ph.D. dissertation, University of Massachusetts at Amherst, 2003.
[7]
R. Child and P. A. Wilsey, "Using dvfs to optimize time warp simulations," in Proceedings of the Winter Simulation Conference. Winter Simulation Conference, 2012, p. 288.
[8]
T. Guérout, T. Monteil, G. Da Costa, R. N. Calheiros, R. Buyya, and M. Alexandru, "Energy-aware simulation with dvfs," Simulation Modelling Practice and Theory, vol. 39, pp. 76--91, 2013.
[9]
M. Curtis-Maury, A. Shah, F. Blagojevic, D. S. Nikolopoulos, B. R. De Supinski, and M. Schulz, "Prediction models for multi-dimensional power-performance optimization on many cores," in Proceedings of the 17th international conference on Parallel architectures and compilation techniques. ACM, 2008, pp. 250--259.
[10]
X. Feng, R. Ge, and K. W. Cameron, "Power and energy profiling of scientific applications on distributed systems," in Parallel and Distributed Processing Symposium, 2005. Proceedings. 19th IEEE International. IEEE, 2005, pp. 10--pp.
[11]
S. Hua and G. Qu, "Approaching the maximum energy saving on embedded systems with multiple voltages," in Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design. IEEE Computer Society, 2003, p. 26.
[12]
C. Lively, V. Taylor, X. Wu, H.-C. Chang, C.-Y. Su, K. Cameron, S. Moore, and D. Terpstra, "E-amom: an energy-aware modeling and optimization methodology for scientific applications," Computer Science-Research and Development, vol. 29, no. 3-4, pp. 197--210, 2014.
[13]
R. M. Fujimoto, M. Hunter, A. Biswas, M. Jackson, and S. Neal, "Power efficient distributed simulation," in Proceedings of the 2017 ACM SIGSIM Conference on Principles of Advanced Discrete Simulation. ACM, 2017, pp. 77--88.
[14]
F. Maqbool, S. M. R. Naqvi, and A. W. Malik, "Why to redesign pdes framework for smart devices: An empirical study," in Proceedings of the Summer Simulation Multi-Conference, ser. SummerSim '17. San Diego, CA, USA: Society for Computer Simulation International, 2017, pp. 20:1--20:11.
[15]
V. Tiwari, S. Malik, A. Wolfe, and M.-C. Lee, "Instruction level power analysis and optimization of software," in VLSI Design, 1996. Proceedings., Ninth International Conference on. IEEE, 1996, pp. 326--328.
[16]
A. Biswas and R. Fujimoto, "Profiling energy consumption in distributed simulations," in Proceedings of the 2016 annual ACM Conference on SIGSIM Principles of Advanced Discrete Simulation. ACM, 2016, pp. 201--209.
[17]
A. W. Malik, I. Mahmood, and A. Parkash, "Energy consumption of traditional simulation protocol over smartphones: an empirical study (wip)," in Proceedings of the Summer Computer Simulation Conference. Society for Computer Simulation International, 2016, p. 23.
[18]
S. Neal, R. Fujimoto, and M. Hunter, "Energy consumption of data driven traffic simulations," in Winter Simulation Conference (WSC), 2016. IEEE, 2016, pp. 1119--1130.
[19]
R. M. Fujimoto, "Research challenges in parallel and distributed simulation," ACM Transactions on Modeling and Computer Simulation (TOMACS), vol. 26, no. 4, p. 22, 2016.
[20]
K. Shenoy, "Techniques for optimizing time-stepped simulations," 2004.
[21]
K. M. Chandy and J. Misra, "Distributed simulation: A case study in design and verification of distributed programs," IEEE Transactions on software engineering, no. 5, pp. 440--452, 1979.
[22]
D. R. Jefferson, "Virtual time," ACM Transactions on Programming Languages and Systems (TOPLAS), vol. 7, no. 3, pp. 404--425, 1985.
[23]
R. M. Fujimoto, "Performance of time warp under synthetic workloads," in Distributed Simulation Conference, Jan 1990, 1990, pp. 23--28.
[24]
V. Madisetti, J. Walrand, and D. Messerschmitt, "Wolf: A rollback algorithm for optimistic distributed simulation systems," in Simulation Conference Proceedings, 1988 Winter. IEEE, 1988, pp. 296--305.

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences
DS-RT '18: Proceedings of the 22nd International Symposium on Distributed Simulation and Real Time Applications
October 2018
283 pages
ISBN:9781538650486

Sponsors

In-Cooperation

  • IEEE TCCA: IEEE Computer Society Technical Committee on Computer Architecture
  • IEEE CS TCPP: IEEE Computer Society Technical Committee on Parallel Processing

Publisher

IEEE Press

Publication History

Published: 15 October 2018

Check for updates

Author Tags

  1. PDES
  2. conservative
  3. mobile devices
  4. optimistic
  5. time warp

Qualifiers

  • Research-article

Conference

DS-RT '18
Sponsor:

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 28
    Total Downloads
  • Downloads (Last 12 months)1
  • Downloads (Last 6 weeks)0
Reflects downloads up to 28 Dec 2024

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media