Skip to main content
SpringerLink
Log in

DPMA: a distributed profit-based placement scheme for multi-sp mobile edge computing

  • Published:
Journal of Combinatorial Optimization Aims and scope Submit manuscript

Abstract

With the development over the past decades, mobile edge computing has been widely used in many fields. Benefit from the low latency brought by the proximity of mobile edge computing to the user side and the relief of bandwidth pressure, mobile edge computing can play a significant role in services with large backhaul traffic such as live video streaming. However, the edge server does not have the same powerful hardware as the cloud server, and the limited resources on the edge server make the deployment of services need to be carefully considered. Small-sized service providers in edge networks may not have their own edge servers and need to rent the edge servers of edge server providers to deploy their own services. In this paper, we present a service provider profit maximization problem under the service scenario of large backhaul traffic. Considering the needs of server providers and service providers, we design a novel method, Distributed Profit-based Matching Algorithm (DPMA), to solve this problem according to the idea of Deferred Acceptance algorithm. The experimental results show that the proposed method is superior to the existing profit maximization methods in mobile edge computing.

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

Similar content being viewed by others

Data Availability

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.

References

  • Andrews JG, Buzzi S, Choi W, Hanly SV, Lozano A, Soong ACK, Zhang JC (2014) What will 5g be? IEEE J Sel Areas Commun 32(6):1065–1082

    Article  Google Scholar 

  • Bahreini T, Grosu D (2020) Efficient algorithms for multi-component application placement in mobile edge computing. IEEE Trans Cloud Comput:1

  • Gale D, Shapley LS (1962) College admissions and the stability of marriage. Am Math Mon 69(1):9–15

    Article  MathSciNet  MATH  Google Scholar 

  • Goudarzi M, Wu H, Palaniswami M, Buyya R (2021) An application placement technique for concurrent iot applications in edge and fog computing environments. IEEE Trans Mob Comput 20(4):1298–1311

    Article  Google Scholar 

  • Huang X, He L, Zhang W (2020) Vehicle speed aware computing task offloading and resource allocation based on multi-agent reinforcement learning in a vehicular edge computing network. IEEE Int Conf Edge Comput (EDGE) 2020:1–8

    Google Scholar 

  • Huang X, Zhang B, Li C (2021) Platform profit maximization on service provisioning in mobile edge computing. IEEE Trans Veh Technol 70(12):13 364-13 376

    Article  Google Scholar 

  • Hung Y-H, Wang C-Y, Hwang R-H (2020) Optimizing social welfare of live video streaming services in mobile edge computing. IEEE Trans Mob Comput 19(4):922–934

    Article  Google Scholar 

  • Kasi SK, Kasi MK, Ali K, Raza M, Afzal H, Lasebae A, Naeem B, Islam S, Rodrigues JJPC (2021) Heuristic edge server placement in industrial internet of things and cellular networks. IEEE Internet Things J 8(13):10 308-10 317

    Article  Google Scholar 

  • Li Y, Zhou A, Ma X, Wang S (2022) Profit-aware edge server placement. IEEE Internet Things J 9(1):55–67

    Article  Google Scholar 

  • Moubayed A, Shami A, Heidari P, Larabi A, Brunner R (2021) Edge-enabled v2x service placement for intelligent transportation systems. IEEE Trans Mob Comput 20(4):1380–1392

    Article  Google Scholar 

  • Raghavendra MS, Chawla P, Rana A (2020) A survey of optimization algorithms for fog computing service placement. In: 2020 8th international conference on reliability, infocom technologies and optimization (trends and future directions) (ICRITO), pp 259–262

  • Shi W, Cao J, Zhang Q, Li Y, Xu L (2016) Edge computing: vision and challenges. IEEE Internet Things J 3(5):637–646

    Article  Google Scholar 

  • Tai Y-C, Yen L-H (2021) Network service embedding in multiple edge systems: profit maximization by federation. In: ICC 2021—IEEE international conference on communications, pp 1–6

  • Van Ma L, Nguyen VQ, Park J, Kim J (2018) Nfv-based mobile edge computing for lowering latency of 4k video streaming. In: Tenth international conference on ubiquitous and future networks (ICUFN), vol 2018, pp 670–673

  • Wang Z, Du H, Ye Q (2021) Htr: a joint approach for task offloading and resource allocation in mobile edge computing. In: ICC 2021—IEEE international conference on communications, pp 1–6

  • Wang Q, Guo S, Liu J, Pan C, Yang L (2019) Profit maximization incentive mechanism for resource providers in mobile edge computing. IEEE Trans Serv Comput:1

  • Xu Z, Zhou L, Chi-Kin Chau S, Liang W, Xia Q, Zhou P (2020) Collaborate or separate? distributed service caching in mobile edge clouds. In: IEEE INFOCOM 2020—IEEE conference on computer communications, pp 2066–2075

  • Ying J, Hsieh J, Hou D, Hou J, Liu T, Zhang X, Wang Y, Pan Y-T (2021) Edge-enabled cloud computing management platform for smart manufacturing. In: 2021 IEEE international workshop on metrology for industry 4.0 IoT (MetroInd4.0 IoT), pp 682–686

  • Yuan H, Zhou M (2021) Profit-maximized collaborative computation offloading and resource allocation in distributed cloud and edge computing systems. IEEE Trans Autom Sci Eng 18(3):1277–1287

    Article  MathSciNet  Google Scholar 

  • Yuan D, Zhu X, Mao Y, Zheng B, Wu T (2019) Privacy-preserving pedestrian detection for smart city with edge computing. In: 2019 11th international conference on wireless communications and signal processing (WCSP), pp 1–6

  • Zeng G, Du H, Ye Q, Zhang C (2021) Collaborative service placement for maximizing the profit in mobile edge computing. IEEE Glob Commun Conf (GLOBECOM) 2021:1–6

    Google Scholar 

  • Zhang C, Du H, Ye Q, Liu C, Yuan H (2019) Dmra: a decentralized resource allocation scheme for multi-sp mobile edge computing. In: 2019 IEEE 39th international conference on distributed computing systems (ICDCS), pp 390–398

  • Zhang Y, Zhang Y (2020) Discussion on key technologies of cloud game based on 5g and edge computing. In: 2020 IEEE 20th international conference on communication technology (ICCT), pp 524–527

Download references

Acknowledgements

This work is supported by National Natural Science Foundation of China (No. 62172124), the Shenzhen Basic Research Program (Project No. JCYJ20190806143011274), the Shenzhen Colleges and Universities Stable Support Program No. GXWD20201230155427003-20200822080602001 and the Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies (2022B1212010005).

Author information

Authors and Affiliations

  1. School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen), Shenzhen, China

    Rui Mao & Hongwei Du

  2. Guangdong Provincial Key Laboratory of Novel Security Intelligence Technologies, Shenzhen, China

    Rui Mao & Hongwei Du

Authors
  1. Rui Mao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hongwei Du
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hongwei Du.

Ethics declarations

Competing interest

The authors have not disclosed any competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mao, R., Du, H. DPMA: a distributed profit-based placement scheme for multi-sp mobile edge computing. J Comb Optim 44, 3294–3309 (2022). https://doi.org/10.1007/s10878-022-00894-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10878-022-00894-7

Keywords

Search

Navigation