Skip to main content
SpringerLink
Log in

Efficient service selection approach for mobile devices in mobile cloud

  • Published:
The Journal of Supercomputing Aims and scope Submit manuscript

Abstract

The paper proposes optimal efficient cloud service selection scheme for mobile device through local and public cloud in hybrid cloud. The proposed model consists of non-dedicated public cloud resources and local cloud resources. At different locations, local cloud service providers maintain finite dedicated resources that can be used by mobile device users. In the proposed model, the system middleware first examines if any of the local cloud servers have sufficient idle capacity to satisfy the desired requirement of mobile application. If the mobile users’ requirement cannot be handled locally, the proposed architecture must choose mobile users’ jobs to burst to the remote public cloud. The decision of when to trigger a cloud burst involves monitoring the system context and workload. A cloud-based service selection optimization is proposed, which can optimize the resource utilization, cloud supplier’s benefit and mobile user’s QoS. The proposed optimization problem is partitioned by local cloud service selection and public cloud resource scheduling, which is implemented by the mobile device, mobile cloud service broker and cloud supplier. A cloud service selection algorithm for mobile device is proposed, which is composed of two sub-algorithms: cloud service selection optimization and cloud resource scheduling optimization. The efficiency of the cloud service selection algorithm for mobile device is tested by experiments.

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
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Xu Y, Mao S (2013) A survey of mobile cloud computing for rich media applications. IEEE Wirel Commun 20(3):46–53

    Article  Google Scholar 

  2. Wu H, Knottenbelt W, Wolter K (2015) Analysis of the energy-response time tradeoff for mobile cloud offloading using combined metrics. In: 27th International Teletraffic Congress, pp 134–142

  3. Zhou X, Sun M, Wang Y, Wu X (2015) A new QoE-driven video cache allocation scheme for mobile cloud server. In: 11th EAI international conference on heterogeneous networking for quality, reliability, security and robustness (QSHINE 2015), pp 122–126

  4. Karadimce A, Davcev D (2015) Building context-rich Mobile Cloud services for Mobile Cloud applications. In: 2nd European conference on social media (ECSM 2015), pp 505–513

  5. Akinola AT, Adigun MO, Akingbesote AO (2015) QoS-aware single service selection mechanism for ad-hoc mobile cloud computing. In: 2015 International conference on computing, communication and security (ICCCS), pp 1–6

  6. Panigrahi CR, Pati B, Tiwary M, Sarkar JL (2015) EEOA: improving energy efficiency of mobile cloudlets using efficient offloading approach. In: 2015 IEEE international conference on advanced networks and telecommunications systems (ANTS), pp 1–6

  7. Kwak J, Kim Y, Lee J, Chong S (2015) DREAM: dynamic resource and task allocation for energy minimization in mobile cloud systems. IEEE J Sel Areas Commun 33(12):2510–2523

    Article  Google Scholar 

  8. Arabnia HR (1995) A distributed stereocorrelation algorithm. In: Fourth international conference on computer communications and networks, pp 479–482

  9. Bhandarkar SM, Arabnia HR (1995) The REFINE multiprocessor—theoretical properties and algorithms. Parallel Comput 21(11):1783–1805

    Article  Google Scholar 

  10. Wani MA, Arabnia HR (2003) Parallel edge-region-based segmentation algorithm targeted at reconfigurable multi-ring network. J Supercomput 25(1):43–62

    Article  MATH  Google Scholar 

  11. Arabnia HR (1990) A parallel algorithm for the arbitrary rotation of digitized images using process-and-data-decomposition approach. J Parallel Distrib Comput 10(2):188–192

    Article  Google Scholar 

  12. Arabnia HR, Oliver MA (1989) A transputer network for fast operations on digitised images. Int J Eurograph Assoc(Comput Graph Forum) 8(1):3–12

  13. Bhandarkar SM, Arabnia HR (1995) The hough transform on a reconfigurable multi-ring network. J Parallel Distrib Comput 24(1):107–114

    Article  Google Scholar 

  14. Arabnia HR, Oliver MA (1987) A transputer network for the arbitrary rotation of digitised images. Comput J 30(5):425–433

    Article  Google Scholar 

  15. Arabnia HR, Oliver MA (1987) Arbitrary rotation of raster images with SIMD machine architectures. Int J Eurograph Assoc (Comput Graph Forum) 6(1):3–12

    Article  Google Scholar 

  16. Arabnia HR, Bhandarkar SM (1996) Parallel stereocorrelation on a reconfigurable multi-ring network. J Supercomput (Springer Publishers) 10(3):243–270

    Article  MATH  Google Scholar 

  17. Arabnia HR, Smith JW (1993) A reconfigurable interconnection network for imaging operations and its implementation using a multi-stage switching box. In: Proceedings of the 7th annual international high performance computing conference. The 1993 high performance computing: new horizons supercomputing symposium, Calgary, Alberta, Canada, June 1993, pp 349–357

  18. Bhandarkar SM, Arabnia HR, Smith JW (1995) A reconfigurable architecture for image processing and computer vision. Int J Pattern Recognit Artif Intell 9(2):201–229

    Article  Google Scholar 

  19. Liu Y, Lee MJ (2015) Adaptive multi-resource allocation for cloudlet-based mobile cloud computing system. IEEE Trans Mob Comput PP(99):1

  20. Ferber M, Rauber T, Torres MHC, Holvoet T (2012) Resource allocation for cloud-assisted mobile applications. In: IEEE fifth international conference on cloud computing, pp 400–407

  21. Nishio T, Shinkuma R, Takahashi T, Mandayam NB (2013) Service-oriented heterogeneous resource sharing for optimizing service latency in mobile cloud. In: International workshop on mobile cloud computing and networking, pp 19–26

  22. Ghouma H, Jaseemuddin M (2015) Context aware resource allocation and scheduling for mobile cloud. In: 2015 IEEE 4th international conference on cloud networking (CloudNet), pp 67–70

  23. Jakimovski G, Karadimce A, Davcev D (2015) Multimedia content delivery between mobile cloud and mobile devices. In: Ad-hoc networks and wireless. The series lecture notes in computer science, vol 8629, pp 3–11

  24. Sindia S, Gao S, Black B, Lim AS, Agrawal V, Agrawal P (2013) MobSched: customizable scheduler for mobile cloud computing. In: 45th Southeastern symposium on system theory, pp 129–134

  25. Nasseri M, Alam M, Green RC (2013) MDP based optimal policy for collaborative processing using mobile cloud computing. In: 2013 IEEE 2nd international conference on cloud networking (CloudNet), pp 123–129

  26. Chen J, Zheng Q, Long H, Wang W (2015) Delay-oriented dynamic control for interactive mobile cloud services. In: 2015 IEEE wireless communications and networking conference (WCNC 2015), pp 896–901

  27. Lin T-Y, Lin T-A, Hsu C-H, King C-T (2013) Context-aware decision engine for mobile cloud offloading. In: IEEE WCNC workshop on mobile cloud computing and networking 2013, pp 111–116

  28. Fiandrino C, Kliazovich D, Bouvry P, Zomaya AY (2015) Network-assisted offloading for mobile cloud applications. In: IEEE ICC 2015—communications QoS, reliability and modeling symposium, pp 5833–5838

  29. Fesehaye D, Gao Y, Nahrstedt K, Wang G (2012) Impact of cloudlets on interactive mobile cloud applications. In: 2012 IEEE 16th international enterprise distributed object computing conference, pp 123–132

  30. Benkhelifa E, Welsh T, Tawalbeh L, Khreishah A, Jararweh Y, Al-Ayyoub M (2016) GA-based resource augmentation negotiation for energy-optimised mobile ad-hoc cloud. In: 2016 5th IEEE international conference on mobile cloud computing, services, and engineering (MobileCloud 2016), pp 1–7

  31. Qin Z, Zhang J, Zhang X (2012) An effective partition approach for elastic application development on MobileCloud Computing. In: Advances in grid and pervasive computing. The series lecture notes in computer science, vol 7296, pp 46–53

  32. Karamoozian A, Hafid A, Boushaba M, Afzali M (2016) QoS-aware resource allocation for mobile media services in cloud environment. In: 2016 13th IEEE annual consumer communications and networking conference (CCNC), pp 732–737

  33. Li C, Li L (2014) Phased scheduling for resource-constrained mobile devices in mobile cloud computing. Wirel Personal Commun 77(4):2817–2837

    Article  Google Scholar 

  34. Li C, Li L (2015) Cost and energy aware service provisioning for mobile client in cloud computing environment. J Supercomput 71(4):1196–1223

    Article  Google Scholar 

  35. Luh PB, Hoitomt DJ (1993) Scheduling of manufacturing systems using the Lagrangian relaxation technique. IEEE Trans Autom Control 38(7):1066–1079

    Article  MathSciNet  Google Scholar 

  36. Kuhn HW, Tucker AW (1951) Nonlinear programming. In: Proceedings of 2nd Berkeley symposium. University of California Press, Berkeley, pp 481–492

  37. Kelly F, Maulloo A, Tan D (1998) Rate control for communication networks: shadow prices, proportional fairness and stability. J Oper Res Soc 49(3):237–252

    Article  MATH  Google Scholar 

Download references

Acknowledgments

The authors thank the editor and the anonymous reviewers for their helpful comments and suggestions. The work was supported by the National Natural Science Foundation (NSF) under grants (No. 61472294), Key Natural Science Foundation of Hubei Province (No. 2014CFA050), Applied Basic Research Project of WuHan (No. 2015010101010021), Program for the High-end Talents of Hubei Province. Any opinions, findings, and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

Author information

Authors and Affiliations

  1. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Chunlin Li & Liu Yanpei

  2. Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou, People’s Republic of China

    Chunlin Li

  3. School of Management, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Luo Youlong

Authors
  1. Chunlin Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Liu Yanpei
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Luo Youlong
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Chunlin Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, C., Yanpei, L. & Youlong, L. Efficient service selection approach for mobile devices in mobile cloud. J Supercomput 72, 2197–2220 (2016). https://doi.org/10.1007/s11227-016-1720-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11227-016-1720-0

Keywords

Search

Navigation