Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/3183767.3183778acmotherconferencesArticle/Chapter ViewAbstractPublication Pagesparma-ditamConference Proceedingsconference-collections
research-article

Enabling Run-Time Managed Distributed Mobile Computing

Published: 23 January 2018 Publication History

Abstract

The increasing pervasiveness of mobile devices combined with their replacement rate, led us to deal with the disposal of an increasing amount of still working electronic devices. This work proposes an approach to mitigate this problem by extending the mobile devices' lifetime, by integrating them as part of a distributed mobile computing system. Thanks also to the growing computational power of such devices, this paradigm opens up the opportunity to deploy mobile applications in a distributed manner. This, without forgetting the energy budget management as a paramount objective. In this work, we built a proof-of-concept, based on the extension of a run-time resource manager to support Android applications. We introduced a energy-aware device selection policy to dispatch the application workload according to both device capabilities and run-time status. Experimental results show that, as well as increasing the utilization of multiple mobile devices available to the single user, using an energy-efficiency and distributed approach can increase the battery duration between 12% and 36%.

References

[1]
ARM. 2013. big.LITTLE Technology: The future of mobile. (2013).
[2]
P. Bellasi, G. Massari, and W. Fornaciari. 2012. A RTRM proposal for multi/manycore platforms and reconfigurable applications. In 7th International Workshop on Reconfigurable and Communication-Centric Systems-on-Chip (ReCoSoC). 1--8.
[3]
Patrick Bellasi, Giuseppe Massari, and William Fornaciari. 2015. Effective Runtime Resource Management Using Linux Control Groups with the BarbequeRTRM Framework. ACM Trans. Embed. Comput. Syst. 14, 2, Article 39 (March 2015), 17 pages.
[4]
G. Calice, A. Mtibaa, R. Beraldi, and H. Alnuweiri. 2015. Mobile-to-mobile opportunistic task splitting and offloading. In 2015 IEEE 11th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). 565--572.
[5]
Y. Chen, E. Macii, and M. Poncino. 2017. A circuit-equivalent battery model accounting for the dependency on load frequency. In Design, Automation Test in Europe Conference Exhibition (DATE), 2017. 1177--1182.
[6]
BenchmarkXPRT Development Community. 2015. MobileXPRT2015. (2015). Retrieved May 8, 2017 from http://www.mobilexprt.com.
[7]
M. Conti, S. Giordano, M. May, and A. Passarella. 2010. From opportunistic networks to opportunistic computing. IEEE Communications Magazine 48, 9 (Sept 2010), 126--139.
[8]
L. Corral, A. B. Georgiev, A. Sillitti, and G. Succi. 2013. A method for characterizing energy consumption in Android smartphones. In 2013 2nd International Workshop on Green and Sustainable Software (GREENS). 38--45.
[9]
T. Coughlin and I. C. E. S. Future Directions Committee. 2015. A Moore?s Law for Mobile Energy: Improving upon conventional batteries and energy sources for mobile devices. IEEE Consumer Electronics Magazine 4, 1 (Jan 2015), 74--82.
[10]
Alan Ferrari, Silvia Giordano, and Daniele Puccinelli. 2016. Reducing Your Local Footprint with Anyrun Computing. Comput. Commun. 81, C (May 2016), 1--11.
[11]
A. Ferrari, D. Puccinelli, and S. Giordano. 2016. Code mobility for on-demand computational offloading. In 2016 IEEE 17th International Symposium on A World of Wireless, Mobile and Multimedia Networks (WoWMoM). 1--6.
[12]
Futuremark. 2015. PCMark2.0. (2015). Retrieved May 8, 2017 from http://www.futuremark.com.
[13]
Hank H. Harvey, Ying Mao, Yantian Hou, and Bo Sheng. 2017. EDOS: Edge Assisted Offloading System for Mobile Devices. In Proceedings of the 26th International Conference on Computer Communications and Networks (ICCCN 2017).
[14]
HiPEAC. 2017. Vision. (2017). Retrieved December 1, 2017 from https://www.hipeac.net/publications/vision.
[15]
S. Holmbacka, E. Nogues, M. Pelcat, S. Lafond, and J. Lilius. 2014. Energy efficiency and performance management of parallel dataflow applications. In Proceedings of the 2014 Conference on Design and Architectures for Signal and Image Processing. 1--8.
[16]
M. Horowitz, T. Indermaur, and R. Gonzalez. 1994. Low-power digital design. In Proceedings of 1994 IEEE Symposium on Low Power Electronics. 8--11.
[17]
Google Inc. 2017. API Guides - App Components - Services. (2017). Retrieved May 6, 2017 from https://developer.android.com/guide/components/services.html.
[18]
Google Inc. 2017. API Guides - App Manifest - <uses-features>. (2017). Retrieved May 4, 2017 from https://developer.android.com/guide/topics/manifest/uses-feature-element.html.
[19]
Google Inc. 2017. API Guides - Platform Architecture. (2017). Retrieved May 6, 2017 from https://developer.android.com/guide/platform/index.html.
[20]
Google Inc. 2017. Permissions. (2017). Retrieved May 4, 2017 from https://developer.android.com/guide/topics/permissions/index.html.
[21]
Gartner institute. 2017. Global Smartphones Sales. (2017). Retrieved May 2, 2017 from https://www.gartner.com.
[22]
Karthik Kumar, Jibang Liu, Yung-Hsiang Lu, and Bharat Bhargava. 2013. A Survey of Computation Offloading for Mobile Systems. Mobile Networks and Applications 18, 1 (2013), 129--140.
[23]
S. Lafond, S. Holmbacka, and J. Lilius. 2016. Energy aware software: Issues, approaches and challenges. In 2016 Seventh International Green and Sustainable Computing Conference (IGSC). 1--8.
[24]
LG and Google Inc. 2013. Nexus 5. (2013). Retrieved May 8, 2017 from http://www.lg.com/us/cell-phones/lg-D820-Sprint-Black-nexus-5.
[25]
S. Libutti, G. Massari, and W. Fornaciari. 2016. Co-scheduling tasks on multi-core heterogeneous systems: An energy-aware perspective. IET Computers Digital Techniques 10, 2 (2016), 77--84.
[26]
F. Lordan and R. M. Badia. 2016. COMPSs-Mobile: Parallel Programming for Mobile-Cloud Computing. In 2016 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid). 497--500.
[27]
C. B. Margi, K. Obraczka, and R. Manduchi. 2005. Characterizing system level energy consumption in mobile computing platforms. In 2005 International Conference on Wireless Networks, Communications and Mobile Computing, Vol. 2. 1142--1147 vol.2.
[28]
Giuseppe Massari, Chiara Caffarri, Patrick Bellasi, and William Fornaciari. 2014. Extending a Run-time Resource Management Framework to Support OpenCL and Heterogeneous Systems. In Proceedings of Workshop on Parallel Programming and Run-Time Management Techniques for Many-core Architectures and Design Tools and Architectures for Multicore Embedded Computing Platforms (PARMA-DITAM '14). ACM, New York, NY, USA, Article 21, 6 pages.
[29]
G. Massari, M. Zanella, and W. Fornaciari. 2016. Towards Distributed Mobile Computing. In 2016 Mobile System Technologies Workshop (MST). 29--35.
[30]
Art Morgan. 2015. Benchmark Selection Guide, vol.1. (2015). Retrieved May 8, 2017 from https://www.k12blueprint.com/sites/default/files/Understanding%20Benchmarks.pdf.
[31]
ODROID. 2014. Smart Power. (2014). Retrieved May 8, 2017 from http://www.hardkernel.com/main/products/prdt_info.php?g_code=G137361754360.
[32]
I. Takouna, W. Dawoud, and C. Meinel. 2011. Accurate Mutlicore Processor Power Models for Power-Aware Resource Management. In 2011 IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing. 419--426.
[33]
International Telecommunication Union. 2016. (2016). Retrieved May 8, 2017 from http://www.itu.int.
[34]
G. Valenzuela, A. Neyem, J. I. Benedetto, J. Navon, P. Sanabria, J. A. Karmy, and F. Balbontin. 2017. Towards Native Code Offloading Platforms for Image Processing in Mobile Applications: A Case Study. In 2017 IEEE/ACM 4th International Conference on Mobile Software Engineering and Systems (MOBILESoft). 221--222.
[35]
Yating Wang, Ing-Ray Chen, and Ding-Chau Wang. 2015. A Survey of Mobile Cloud Computing Applications: Perspectives and Challenges. Wireless Personal Communications 80, 4 (2015), 1607--1623.
[36]
Ibrar Yaqoob, Ejaz Ahmed, Abdullah Gani, Salimah Mokhtar, Muhammad Imran, and Sghaier Guizani. 2016. Mobile Ad Hoc Cloud: A Survey. Wirel. Commun. Mob. Comput. 16, 16 (2016), 2572--2589.

Cited By

View all
  • (2023)Minus HELLO: HELLO Devoid Protocols for Energy Preservation in Mobile Ad-hoc NetworksSustainable Computing: Informatics and Systems10.1016/j.suscom.2023.10085238(100852)Online publication date: Apr-2023
  • (2022)Post-cloud Computing: Addressing Resource Management in the Resource ContinuumSpecial Topics in Information Technology10.1007/978-3-031-15374-7_9(105-115)Online publication date: 11-Nov-2022
  • (2021)Managing the Resource Continuum in a Real Video Surveillance Scenario2021 24th Euromicro Conference on Digital System Design (DSD)10.1109/DSD53832.2021.00018(58-61)Online publication date: Sep-2021
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Other conferences
PARMA-DITAM '18: Proceedings of the 9th Workshop and 7th Workshop on Parallel Programming and RunTime Management Techniques for Manycore Architectures and Design Tools and Architectures for Multicore Embedded Computing Platforms
January 2018
76 pages
ISBN:9781450364447
DOI:10.1145/3183767
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

In-Cooperation

  • HiPEAC: HiPEAC Network of Excellence

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 January 2018

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. Distributed Systems
  2. Mobile Cloud Computing
  3. Mobile Computing
  4. Portable devices
  5. Resource Management

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Funding Sources

  • H2020-FETHPC-2014

Conference

PARMA-DITAM '18

Acceptance Rates

Overall Acceptance Rate 11 of 24 submissions, 46%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)2
  • Downloads (Last 6 weeks)0
Reflects downloads up to 09 Nov 2024

Other Metrics

Citations

Cited By

View all
  • (2023)Minus HELLO: HELLO Devoid Protocols for Energy Preservation in Mobile Ad-hoc NetworksSustainable Computing: Informatics and Systems10.1016/j.suscom.2023.10085238(100852)Online publication date: Apr-2023
  • (2022)Post-cloud Computing: Addressing Resource Management in the Resource ContinuumSpecial Topics in Information Technology10.1007/978-3-031-15374-7_9(105-115)Online publication date: 11-Nov-2022
  • (2021)Managing the Resource Continuum in a Real Video Surveillance Scenario2021 24th Euromicro Conference on Digital System Design (DSD)10.1109/DSD53832.2021.00018(58-61)Online publication date: Sep-2021
  • (2019)Run-Time Managed Mobile Application Execution2019 Fourth International Conference on Fog and Mobile Edge Computing (FMEC)10.1109/FMEC.2019.8795323(74-77)Online publication date: Jun-2019
  • (2018)Back to the futureProceedings of the Workshop on INTelligent Embedded Systems Architectures and Applications10.1145/3285017.3285028(33-38)Online publication date: 4-Oct-2018

View Options

Get Access

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