Collaborative Service Placement for Mobile Edge Computing Applications

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

15 Scopus Citations
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Author(s)

  • Nuo Yu
  • Qingyuan Xie
  • Qiuyun Wang
  • Hongwei Du
  • Hejiao Huang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publication2018 IEEE Global Communications Conference (GLOBECOM) - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538647271
Publication statusPublished - Dec 2018

Publication series

NameIEEE Global Communications Conference, GLOBECOM - Proceedings
ISSN (Electronic)2576-6813

Conference

TitleIEEE Global Communications Conference (IEEE GLOBECOM 2018)
LocationAbu Dhabi National Exhibition Centre (ADNEC)
PlaceUnited Arab Emirates
CityAbu Dhabi
Period9 - 13 December 2018

Abstract

Mobile edge computing (MEC) can improve the quality of services and save the bandwidth of backhual networks, by placing application services in the base stations (BSS), which are endowed with computing resources and are in close proximity to user equipments (UEs). Since the capacity of an individual BS is limited, only a small number of service instances can be allowed for each BS at the same time. Meanwhile, in a densely deployed network, the coverage areas of adjacent BSS are overlapped. Therefore, these capacity-limited BSS can collaboratively optimize their service placements to improve the performance of MEC. In this paper, we investigate the collaborative service placement (CSP) problem in MEC, which aims to minimize the traffic load caused by service request forwarding. The CSP problem involves several difficult issues, including correlations of adjacent BSS' service placement decisions, joint service placement and UE association, and joint allocation of computing and radio resources. This makes the CSP problem be a complex combinatorial optimization problem. To solve the CSP problem, we propose an efficient decentralized algorithm based on the Matching Theory. It can optimize the decisions of service placement and BS-UE association for BSS, according to local interactions between BSS and UEs. Our proposed algorithm is practical for large-size networks, and its effectiveness is demonstrated by the simulation results.

Research Area(s)

  • cellular networks, Matching Theory, Mobile edge computing, service placement

Citation Format(s)

Collaborative Service Placement for Mobile Edge Computing Applications. / Yu, Nuo; Xie, Qingyuan; Wang, Qiuyun; Du, Hongwei; Huang, Hejiao; Jia, Xiaohua.

2018 IEEE Global Communications Conference (GLOBECOM) - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8647338 (IEEE Global Communications Conference, GLOBECOM - Proceedings).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review