Total views : 225

An Energy Efficient Code Offloading Approach for Mobile Cloud Computing

Affiliations

  • School of Computing, SASTRA University, Thanjavur - 613401, Tamil Nadu, India

Abstract


Objectives: This research work proposes a methodology for estimating the energy consumption of tasks by considering processor and memory usage. Methods: To facilitate energy efficiency in CPU, the mobile devices may be operated at different frequencies during the execution of tasks. This research work applies CPU frequency scaling as its base to achieve energy efficiency. Besides, it also considers energy consumption during memory access while making the offloading decision. Findings: The proposed approach uses energy consumption during computation as well as memory access as its metric to conceive the offloading decision. Additionally, the proposed energy model is simulated and the results are concluded that there is a considerable amount of energy saving in mobile devices due to computation offloading to nearby mobile devices or cloud resources. Applications: To save energy decide which application in mobile as energy consume considered as model. The models work as code offloading in MATLAB and determine by two level genetic algorithms. The efficiency of proposed model is evaluated by a simulation and average energy result can be concluded for a mobile device.

Keywords

Frequency Scaling, Mobile Cloud Computing, Offloading, Task Interaction Graph.

Full Text:

 |  (PDF views: 188)

References


  • Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I. Cloud Computing and emerging IT platforms: Vision, hype and reality for delivering computing as the 5th Utility.Future Generation Computer Systems. 2009 Jun; 25(6):599– 616.
  • Gordon MS. Code offload by migrating execution transparently.10th USENIX Symposium on Operating Systems Design and Implementation (OSDI ’12); 2012. p. 1–14.
  • Flores H, Srirama SN. Adaptive code offloading and resourceintensive task delegation for mobile cloud applications.Proceeding 4th ACM workshop on Mobile Cloud Computing and services (MCS ‘13); ACM, New York, NY, USA. 2013. p. 9–16.
  • Flores H, Srirama SN, Paniagua C. A generic middleware framework for handling process intensive hybrid cloud services from mobiles. Proceedings of the 9th International Conference on Advances in Mobile Computing and Multimedia; 2011. p. 87–94.
  • Magurawalage CMS, Yang K. Energy-efficient and networkaware offloading algorithm for Mobile Cloud Computing.Computer Networks. 2014 Dec; 74:22–33.
  • Balakrishnan P, Tham CK. Energy-efficient mapping and scheduling of task interaction graphs for code offloading in Mobile Cloud Computing. Proceedings of the 2013 IEEE/ ACM 6th International Conference on Utility and Cloud Computing; 2013. p. 34–41.
  • Ali FA, Simoensa P, Verbelen T, Demeester P, Dhoedta B.Mobile device power models for energy efficient dynamic offloading at runtime. Journal of Systems and Software.2016 Mar; 113:173–87.
  • Zhang L, Tiwana B, Qiany Z, Wang Z, Dick RP. Accurate online power estimation and automatic battery behavior based power model generation for smart phones. CODES/ ISSS ‘10 Proceedings of the Eighth IEEE/ACM/IFIP International Conference on Hardware/Software Codesign and System Synthesis; 2010. p. 105–14.
  • Chun BG, Ihm S, Maniatis P. Clone cloud: Elastic execution between mobile device and cloud. EuroSys ‘11 Proceedings of the Sixth Conference on Computer Systems; 2011. p.301–4.
  • Shyamala K, Sunitha Rani T. An analysis on efficient resource allocation mechanisms in Cloud Computing. Indian Journal of Science and Technology. 2015 May; 8(9):814–21.
  • Jeon H, Min YG, Seo KK. A performance measurement framework of cloud storage services. Indian Journal of Science and Technology. 2015 Apr; 8(S8):105–11.
  • Balasubramanian N, Balasubramanian A, Venkataramani A. Energy consumption in mobile phones: Measurement, design implications and algorithms. IMC ‘09 Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference; 2009. p. 280–93.

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.