Skip to main content

Advertisement

SpringerLink
Log in

Tradeoff between execution speedup and reliability for compute-intensive code offloading in mobile device cloud

  • Special Issue Paper
  • Published:
Multimedia Systems Aims and scope Submit manuscript

Abstract

With the advent of different mobile computing technologies, mobile devices have opened up a plethora of computational infrastructure to provide improved performance for compute-intensive applications to the end users. Mobile Device Cloud (MDC) technology brings the code offloading mechanism from distant cloud to neighbor mobile devices. However, the major challenges of code offloading in MDC systems include maximization of computation speedup and reliability; unfortunately, these two performance parameters often oppose each other. In this paper, an optimization framework, namely TESAR, has been devised to tradeoff between application execution speedup and reliability while maintaining device energy within a predefined range. We also provide an algorithm for developing a dependency tree among the modules of an application so as to allow higher number of parallel executions, wherever and whenever it is possible. The emulation results of the proposed algorithm outperform the relevant state-of-the-art works in terms of application completion time, communication latency and rescheduling overhead.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. Conti, M., Mascitti, D., Passarella, A.: Offloading service provisioning on mobile devices in mobile cloud computing environments. In: European Conference on Parallel Processing, pp. 299–310. Springer, New York (2015)

    Chapter  Google Scholar 

  2. http://www.statista.com/topics/1002/mobile-app-usage/. Mobileapp usage overview. Access Date 10 Feb 2017

  3. Murray, D.G., Yoneki, E., Crowcroft, J., Hand, S.: The case for crowd computing. In: Proceedings of the Second ACM SIGCOMM Workshop On Networking, Systems, and Applications on Mobile Handhelds, pp. 39–44. ACM (2010)

  4. Cuervo, E., Balasubramanian, A., Cho, D.-k., Wolman, A., Saroiu, S., Chandra, R., Bahl, P.: Maui: making smartphones last longer with code offload. In: Proceedings of the 8th International Conference on Mobile Systems, Applications, and Services, pp. 49–62. ACM (2010)

  5. Kosta, S., Aucinas, A., Hui, P., Mortier, R., Zhang, X., Thinkair: Dynamic resource allocation and parallel execution in the cloud for mobile code offloading. In: INFOCOM, 2012 Proceedings IEEE, pp. 945–953. IEEE (2012)

  6. Huang, D., Wang, P., Niyato, D.: A dynamic offloading algorithm for mobile computing. Wirel. Commun. IEEE Trans. 11(6), 1991–1995 (2012)

    Article  Google Scholar 

  7. Yang, L., Cao, J., Yuan, Y., Li, T., Han, A., Chan, A.: A framework for partitioning and execution of data stream applications in mobile cloud computing. ACM SIGMETRICS Perform. Eval. Rev. 40(4), 23–32 (2013)

    Article  Google Scholar 

  8. Jia, M., Cao, J., Yang, L.: Heuristic offloading of concurrent tasks for computation-intensive applications in mobile cloud computing. In: Computer Communications Workshops (INFOCOM WKSHPS), 2014 IEEE Conference on IEEE, pp. 352–357 (2014)

  9. Qian, H., Andresen, D.: Extending mobile device’s battery life by offloading computation to cloud. In: Mobile Software Engineering and Systems (MOBILESoft), 2015 2nd ACM International Conference on, IEEE, pp. 150–151 (2015)

  10. Cheng, Z., Li, P., Wang, J., Guo, S.: Just-in-time code offloading for wearable computing. Emerg. Topics Comput. IEEE Trans. 3(1), 74–83 (2015)

    Article  Google Scholar 

  11. Khoda, M.E., Razzaque, M.A., Almogren, A., Hassan, M.M., Alamri, A., Alelaiwi, A.: Efficient computation offloading decision in mobile cloud computing over 5g network. Mob. Netw. Appl. 21(5), 777–792 (2016)

    Article  Google Scholar 

  12. Mtibaa, A., Harras, K., Fahim, A., et al.: Towards computational offloading in mobile device clouds. In: Cloud Computing Technology and Science (CloudCom), 2013 IEEE 5th International Conference, vol. 1, pp. 331–338. IEEE (2013)

  13. Mtibaa, A., Harras, K.A., Habak, K., Ammar, M., Zegura, E.W.: Towards mobile opportunistic computing. In: Cloud Computing (CLOUD), 2015 IEEE 8th International Conference on IEEE, pp. 1111–1114 (2015)

  14. Li, J., Bu, K., Liu, X., Xiao, B.: ENDA: embracing network inconsistency for dynamic application offloading in mobile cloud computing. In: Proceedings of the Second ACM SIGCOMM Workshop on Mobile Cloud Computing, pp. 39–44. ACM (2013)

  15. Kulkarni, V., Moro, A., Garbinato, B.: Mobidict: a mobility prediction system leveraging realtime location data streams. In: Proceedings of the 7th ACM SIGSPATIAL International Workshop on GeoStreaming, p. 8. ACM (2016)

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

    Article  Google Scholar 

  17. Jararweh, Y., Tawalbeh, L., Ababneh, F., Dosari, F.: Resource efficient mobile computing using cloudlet infrastructure. In: Mobile Ad-hoc and Sensor Networks (MSN), 2013 IEEE Ninth International Conference on IEEE, pp. 373–377 (2013)

  18. Zhang, Y., Niyato, D., Wang, P., Tham, C.-K.: Dynamic offloading algorithm in intermittently connected mobile cloudlet systems. In: IEEE International Conference on Communications (ICC), pp. 4190–4195. IEEE (2014)

  19. Mahmud, M.R., Afrin, M., Razzaque, M.A., Hassan, M.M., Alelaiwi, A., Alrubaian, M.: Maximizing quality of experience through context-aware mobile application scheduling in cloudlet infrastructure. Softw. Pract. Exp. 46(11), 1525–1545 (2016)

    Article  Google Scholar 

  20. Chen, X., Jiao, L., Li, W., Fu, X.: Efficient multi-user computation offloading for mobile-edge cloud computing. IEEE/ACM Trans. Netw. 24(5), 2795–2808 (2016)

    Article  Google Scholar 

  21. Wang, C., Li, Y., Jin, D.: Mobility-assisted opportunistic computation offloading. Commun. Lett. IEEE 18(10), 1779–1782 (2014)

    Article  Google Scholar 

  22. Drolia, U., Martins, R., Tan, J., Chheda, A., Sanghavi, M., Gandhi, R.,  Narasimhan, P.: The case for mobile edge-clouds. In: Ubiquitous Intelligence and Computing, 2013 IEEE 10th International Conference on and 10th International Conference on Autonomic and Trusted Computing (UIC/ATC), , pp. 209–215. IEEE (2013)

  23. Bhardwaj, K., Sreepathy, S., Gavrilovska, A., Schwan, K.: Ecc: edge cloud composites. In: Mobile Cloud Computing, Services, and Engineering (MobileCloud), 2014 2nd IEEE International Conference on IEEE, pp. 38–47 (2014)

  24. Fernando, N., Loke, S.W., Rahayu, W.: Computing with nearby mobile devices: a work sharing algorithm for mobile edge-clouds. IEEE Trans. Cloud Comput. 99, 1–1 (2016)

  25. Huerta-Canepa, G., Lee, D.: A virtual cloud computing provider for mobile devices. In: Proceedings of the 1st ACM Workshop on Mobile Cloud Computing & Services: Social Networks and Beyond, p. 6. ACM (2010)

  26. Shi, C., Lakafosis, V., Ammar, M.H., Zegura, E.W.: Serendipity: enabling remote computing among intermittently connected mobile devices. In: Proceedings of the Thirteenth ACM International Symposium on Mobile Ad Hoc Networking and Computing, pp. 145–154. ACM (2012)

  27. Shi, C., Ammar, M.H., Zegura, E.W., Naik, M.: Computing in cirrus clouds: the challenge of intermittent connectivity. In: Proceedings of the first edition of the MCC workshop on mobile cloud computing, pp. 23–28. ACM (2012)

  28. Barroso, L.A., Hölzle, U.: The case for energy-proportional computing. Computer 40(12), 33–37 (2007)

    Article  Google Scholar 

  29. Carroll, A., Heiser, G.: An analysis of power consumption in a smartphone. In: USENIX Annual Technical Conference, vol. 14. Boston (2010)

  30. Rodríguez, J.M., Mateos, C., Zunino, A.: Are smartphones really useful for scientific computing? In: International Conference on Advances in New Technologies, Interactive Interfaces, and Communicability, pp. 38–47. Springer, New York (2011)

    Chapter  Google Scholar 

  31. Ren, J., Zhang, Y., Zhang, K., Shen, X.: Exploiting mobile crowdsourcing for pervasive cloud services: challenges and solutions. IEEE Commun. Mag. 53(3), 98–105 (2015)

    Article  Google Scholar 

  32. Saha, S., Habib, M.A., Razzaque, M.A.: Compute intensive code offloading in mobile device cloud. In: Region 10 Conference (TENCON), 2016 IEEE, pp. 436–440. IEEE (2016)

  33. Chun, B.-G., Maniatis, P.: Augmented smartphone applications through clone cloud execution. In: Proceedings of the 12th Conference On Hot Topics in Operating Systems, USENIX Association, pp. 8 (2009)

  34. Marinelli, E.E.: Hyrax: Cloud Computing on Mobile Devices Using Mapreduce, Citeseer (2009)

  35. Fahim, A., Mtibaa, A., Harras, K.A.: Making the case for computational offloading in mobile device clouds. In: Proceedings of the 19th Annual International Conference on Mobile Computing & Networking, pp. 203–205. ACM (2013)

  36. Fernando, N., Loke, S.W., Rahayu, W.: Honeybee: a programming framework for mobile crowd computing. In: International Conference on Mobile and Ubiquitous Systems: Computing, Networking, and Services, pp. 224–236. Springer, New York (2012)

    Google Scholar 

  37. Fernando, N., Loke, S.W., Rahayu, J.W.: Mobile crowd computing with work stealing. In: NBiS, pp. 660–665 (2012)

  38. Habak, K., Ammar, M., Harras, K.A., Zegura, E.: Femto clouds: Leveraging mobile devices to provide cloud service at the edge. In: 2015 IEEE 8th International Conference on Cloud Computing, pp. 9–16 . IEEE (2015)

  39. http://www.neos-server.org/neos/N. optimization server. Access Date: 10 Feb 2017

  40. Hassan, M.M., Song, B., Hossain, M.S., Alamri, A., Alnuem, M.A., Monowar, M.M., Hossain, M.A.: Efficient virtual machine resource management for media cloud computing. TIIS 8(5), 1567–1587 (2014)

  41. http://www.tp-link.com.bd/products/details/cat-15-TD-W8901N.htmlTP-Link TD-W8901N Wireless Router Specification. Access Date: 10 Feb 2017

Download references

Acknowledgements

Special thanks to the Information and Communication Technology Department of the Government of Bangladesh for student fellowship.

Author information

Authors and Affiliations

  1. Green Networking Research Group, Department of Computer Science and Engineering, University of Dhaka, Dhaka, Bangladesh

    Sajeeb Saha, Md. Ahsan Habib, Tamal Adhikary, Md. Abdur Razzaque & Md. Mustafizur Rahman

Authors
  1. Sajeeb Saha
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Md. Ahsan Habib
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Tamal Adhikary
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Md. Abdur Razzaque
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Md. Mustafizur Rahman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Md. Abdur Razzaque.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saha, S., Habib, M.A., Adhikary, T. et al. Tradeoff between execution speedup and reliability for compute-intensive code offloading in mobile device cloud. Multimedia Systems 25, 577–589 (2019). https://doi.org/10.1007/s00530-017-0563-8

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00530-017-0563-8

Keywords

Search

Navigation