Task Offloading in Edge-Clouds with Budget Constraint

  • Lei He
  • Hongli XuEmail author
  • Haibo Wang
  • Liusheng Huang
  • Jingyi Ma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11336)


Edge computing is an emerging computing model that extends the cloud and its services to the edge of network. In edge-cloud computing, a set of servers are deployed near the mobile devices such that these devices can offload tasks to the servers with low latency. Most existing works usually focus on offloading tasks under the premise that sufficient resources are owned by edge servers while ignoring budget constraint of user. If failed to consider about this, the existing offloading schemes may cause user to overspend, this is unacceptable to user. Thus, in this paper, we investigate the task offloading problem in edge-cloud computing aiming to minimize the task duration while tasks are generated by user with constrainted budget. Besides edge servers are equipped with limited computation and storage resources. Specifically, the problem we formulate is an NP-hard problem. In order to solve it, we propose a heuristic strategy. The simulation results prove that the proposed scheme can improve the success ratio and reduce the task duration, compared to random and greedy offloading schemes.


Edge computing Task offloading Budget constraint 



This paper is supported by the NSFC under Grant No. 61472383, U1709217, and 61472385, and the Natural Science Foundation of Jiangsu Province in China under No. BK20161257.


  1. 1.
    Networking, V.: Cisco visual networking index: Global mobile data traffic forecast update, 2014-2019 white paperGoogle Scholar
  2. 2.
    Chen, Z., et al.: An empirical study of latency in an emerging class of edge computing applications for wearable cognitive assistance. In: SEC, p. 14 (2017)Google Scholar
  3. 3.
    Hu, Y.C., Patel, M., Sabella, D., Sprecher, N., Young, V.: Mobile edge computing–a key technology towards 5G. ETSI White Pap. 11(11), 1–16 (2015)Google Scholar
  4. 4.
    Truong, N.B., Lee, G.M., Ghamri-Doudane, Y.: Software defined networking-based vehicular adhoc network with fog computing. In: IFIP/IEEE International Symposium on Integrated Network Management (IM), pp. 1202–1207 (2015)Google Scholar
  5. 5.
    Barbera, M.V., Kosta, S., Mei, A., Stefa, J.: To offload or not to offload? the bandwidth and energy costs of mobile cloud computing. In: Proceedings IEEE INFOCOM, pp. 1285–1293, April 2013Google Scholar
  6. 6.
    Taleb, T., Samdanis, K., Mada, B., Flinck, H., Dutta, S., Sabella, D.: On multi-access edge computing: a survey of the emerging 5G network edge cloud architecture and orchestration. IEEE Commun. Surv. Tutor. 19(3), 1657–1681 (2017)CrossRefGoogle Scholar
  7. 7.
    Zhang, S., Zhang, N., Zhou, S., Gong, J., Niu, Z., Shen, X.: Energy-aware traffic offloading for green heterogeneous networks. IEEE J. Sel. Areas Commun. 34(5), 1116–1129 (2016)CrossRefGoogle Scholar
  8. 8.
    Tan, H., Han, Z., Li, X.Y., Lau, F.C.M.: Online job dispatching and scheduling in edge-clouds. In: IEEE INFOCOM 2017 - IEEE Conference on Computer Communications, pp. 1–9, May 2017Google Scholar
  9. 9.
    Tong, L., Li, Y., Gao, W.: A hierarchical edge cloud architecture for mobile computing. In: IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications, pp. 1–9, April 2016Google Scholar
  10. 10.
    You, C., Huang, K., Chae, H., Kim, B.H.: Energy-efficient resource allocation for mobile-edge computation offloading. IEEE Trans. Wirel. Commun. 16(3), 1397–1411 (2017)CrossRefGoogle Scholar
  11. 11.
    Chen, M., Hao, Y.: Task offloading for mobile edge computing in software defined ultra-dense network. IEEE J. Sel. Areas Commun. 36(3), 587–597 (2018)MathSciNetCrossRefGoogle Scholar
  12. 12.
    Chun, B.G., Ihm, S., Maniatis, P., Naik, M., Patti, A.: Clonecloud: elastic execution between mobile device and cloud. In: Proceedings of the Sixth Conference on Computer systems, pp. 301–314. ACM (2011)Google Scholar
  13. 13.
    Claffy, K.C., Polyzos, G.C., Braun, H.W.: Application of sampling methodologies to network traffic characterization. In: ACM SIGCOMM Computer Communication Review, vol. 23, pp. 194–203. ACM (1993)Google Scholar
  14. 14.
    Gordon, M.S., Jamshidi, D.A., Mahlke, S.A., Mao, Z.M., Chen, X.: Comet: code offload by migrating execution transparently. OSDI 12, 93–106 (2012)Google Scholar
  15. 15.
    Taleb, T., Dutta, S., Ksentini, A., Iqbal, M., Flinck, H.: Mobile edge computing potential in making cities smarter. IEEE Commun. Mag. 55(3), 38–43 (2017)CrossRefGoogle Scholar
  16. 16.
    Jia, M., Cao, J., Liang, W.: Optimal cloudlet placement and user to cloudlet allocation in wireless metropolitan area networks. IEEE Trans. Cloud Comput. 5(4), 725–737 (2017)CrossRefGoogle Scholar
  17. 17.
    Urgaonkar, R., Wang, S., He, T., Zafer, M., Chan, K., Leung, K.K.: Dynamic service migration and workload scheduling in edge-clouds. Perform. Eval. 91, 205–228 (2015)CrossRefGoogle Scholar
  18. 18.
    Xiao, Y., Krunz, M.: Qoe and power efficiency tradeoff for fog computing networks with fog node cooperation. In: IEEE INFOCOM 2017 - IEEE Conference on Computer Communications, pp. 1–9, May 2017Google Scholar
  19. 19.
    Tran, T.X., Pompili, D.: Joint task offloading and resource allocation for multi-server mobile-edge computing networks (2017). arXiv preprint arXiv:1705.00704
  20. 20.
    Sakellariou, R., Zhao, H., Tsiakkouri, E., Dikaiakos, M.D.: Scheduling workflows with budget constraints. Integrated Research in GRID Computing, pp. 189–202. Springer, Boston (2007). Scholar
  21. 21.
    Oprescu, A.M., Kielmann, T.: Bag-of-tasks scheduling under budget constraints. In: 2010 IEEE Second International Conference on Cloud Computing Technology and Science, pp. 351–359, November 2010Google Scholar
  22. 22.
    Zhu, Q., Agrawal, G.: Resource provisioning with budget constraints for adaptive applications in cloud environments. In: Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing, HPDC 2010, pp. 304–307. ACM, New York (2010)Google Scholar
  23. 23.
    Gharooni-fard, G., Moein-darbari, F., Deldari, H., Morvaridi, A.: Scheduling of scientific workflows using a chaos-genetic algorithm. Procedia Comput. Sci. 1(1), 1445–1454 (2010)CrossRefGoogle Scholar
  24. 24.
    Bittencourt, L.F., Madeira, E.R.M.: Hcoc: a cost optimization algorithm for workflow scheduling in hybrid clouds. J. Internet Serv. Appl. 2(3), 207–227 (2011)CrossRefGoogle Scholar
  25. 25.
    Byun, E.K., Kee, Y.S., Kim, J.S., Maeng, S.: Cost optimized provisioning of elastic resources for application workflows. Futur. Gener. Comput. Syst. 27(8), 1011–1026 (2011)CrossRefGoogle Scholar
  26. 26.
    Li, J., Su, S., Cheng, X., Huang, Q., Zhang, Z.: Cost-conscious scheduling for large graph processing in the cloud. In: IEEE International Conference on High Performance Computing and Communications, pp. 808–813, September 2011Google Scholar
  27. 27.
    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)CrossRefGoogle Scholar
  28. 28.
    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)CrossRefGoogle Scholar
  29. 29.
    Sun, Y., Zhou, S., Xu, J.: EMM: Energy-aware mobility management for mobile edge computing in ultra dense networks. IEEE J. Sel. Areas Commun. 35(11), 2637–2646 (2017)CrossRefGoogle Scholar
  30. 30.
    Wu, C.Q., Lin, X., Yu, D., Xu, W., Li, L.: End-to-end delay minimization for scientific workflows in clouds under budget constraint. IEEE Trans. Cloud Comput. 3(2), 169–181 (2015)CrossRefGoogle Scholar
  31. 31.
    Tawalbeh, L.A., Jararweh, Y., Ababneh, F., Dosari, F.: Large scale cloudlets deployment for efficient mobile cloud computing. JNW 10, 70–76 (2015)CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Lei He
    • 1
  • Hongli Xu
    • 1
    Email author
  • Haibo Wang
    • 1
  • Liusheng Huang
    • 1
  • Jingyi Ma
    • 2
  1. 1.Department of Computer Science and TechnologyUniversity of Science and Technology of China (USTC)HefeiChina
  2. 2.TianPing College of SuZhou University of Science and TechnologySuZhouChina

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