Advertisement

Minimum Cost Offloading Decision Strategy for Collaborative Task Execution of Platooning Assisted by MEC

  • Taiping CuiEmail author
  • Xiayan Fan
  • Chunyan Cao
  • Qianbin Chen
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 262)

Abstract

In this paper, we study the offloading decision of collaborative task execution between platoon and MEC (Mobile Edge Computing) server. The mobile application is represented by a series of fine-grained tasks that form a linear topology, each of which is either executed on a local vehicle, offloaded to other members of the platoon, or offloaded to a MEC server. The objective of the design is to minimize the cost of task offloading and meet the deadline of tasks execution. We transform the cost minimized task decision problem into the shortest path problem, which is limited by the deadline of the tasks on a directed acyclic graph. The classical LARAC algorithm is used to solve the problem approximately. Numerical analysis shows that the scheduling method of the tasks decision can be well applied to the platoon scenario and execute the task in cooperation with the MEC server. In addition, compared with different execution models, the optimal offloading decision for collaborative task execution can significantly reduce the cost of task execution and meet lower deadlines.

Keywords

Platooning Mobile edge computing Offloading decision 

References

  1. 1.
    Shah, S.A.A., Ahmed, E., Imran, M., Zeadally, S.: 5G for Vehicular Communications. IEEE Commun. Mag. 56(1), 111–117 (2018)CrossRefGoogle Scholar
  2. 2.
    Mao, Y., You, C., Zhang, J., Huang, K., Letaief, K.B.: A survey on mobile edge computing: the communication perspective. IEEE Commun. Surv. Tutor. 19(4), 2322–2358 (2017). FourthquarterGoogle Scholar
  3. 3.
    Zhang, W., Wen, Y., Wu, D.O.: Energy-efficient scheduling policy for collaborative execution in mobile cloud computing. In: Proceedings IEEE INFOCOM, pp. 190–194. Turin (2013)Google Scholar
  4. 4.
    Zhang, K., Mao, Y., Leng, S., Maharjan, S., Zhang, Y.: Optimal delay constrained offloading for vehicular edge computing networks. In: 2017 IEEE International Conference on Communications (ICC), pp. 1–6. Paris (2017)Google Scholar
  5. 5.
    Khaksari, M., Fischione, C.: Performance analysis and optimization of the joining protocol for a platoon of vehicles. In: 5th International Symposium on Communications. Control and Signal Processing, pp. 1–6. Rome (2012)Google Scholar
  6. 6.
    Shao, C., Leng, S., Zhang, Y., Vinel, A., Jonsson, M.: Analysis of connectivity probability in platoon-based Vehicular Ad Hoc Networks. In: International Wireless Communications and Mobile Computing Conference (IWCMC), pp. 706–711. Nicosia (2014)Google Scholar
  7. 7.
    Karedal, J., Czink, N., Paier, A., Tufvesson, F., Molisch, A.F.: Path loss modeling for vehicle-to-vehicle communications. IEEE Trans. Veh. Technol. 60(1), 323C328 (2011)CrossRefGoogle Scholar
  8. 8.
    Lyu, X., Tian, H., Sengul, C., Zhang, P.: Multiuser joint task offloading and resource optimization in proximate clouds. IEEE Trans. Veh. Technol. 66(4), 3435–3447 (2017)CrossRefGoogle Scholar
  9. 9.
    Wang, Z., Crowcroft, J.: Quality-of-service routing for supporting multimedia applications. IEEE J. Sel. Areas Commun. 14(7), 1228C1234 (1996)Google Scholar
  10. 10.
    Juttner, A., Szviatovski, B., Mecs, I., Rajk o, Z.: Lagrange relaxation based method for the qos routing problem. In: Proceedings of IEEE INFOCOM, vol. 2, pp. 859C868 (2001)Google Scholar
  11. 11.
    Miettinen, A.P., Nurminen, J.K.: Energy efficiency of mobile clients in cloud computing. In: Proceedings of 2nd USENIX Conference Hot Topics Cloud Computer, p. 4 (2010)Google Scholar
  12. 12.
    TD-LTE Carrier Aggregation White Paper. http://lte-tdd.org/. Accessed 12 Jun 2018
  13. 13.
    Widyono, R.: The design and evaluation of routing algorithms for realtime channels. Technical Report TR-94-024, University of California at Berkeley, June 1994Google Scholar

Copyright information

© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2019

Authors and Affiliations

  • Taiping Cui
    • 1
    Email author
  • Xiayan Fan
    • 1
  • Chunyan Cao
    • 1
  • Qianbin Chen
    • 1
  1. 1.School of Communication and Information EngineeringChongqing University of Posts and TelecommunicationsChongqingChina

Personalised recommendations