Energy efficient mobile edge computing in dense cellular networks

Lixing Chen, Sheng Zhou, Jie Xu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Scopus citations


Merging Mobile Edge Computing (MEC), which is an emerging paradigm to meet the increasing computation demands from mobile devices, with the dense deployment of Base Stations (BSs), is foreseen as a key step towards the next generation mobile networks. However, new challenges arise for designing energy efficient networks since radio access resources and computing resources of BSs have to be jointly managed, and yet they are complexly coupled with traffic in both spatial and temporal domains. In this paper, we address the challenge of incorporating MEC into dense cellular networks, and propose an efficient online algorithm, called ENGINE (ENerGy constrained offloadINg and slEeping) which makes joint computation offloading and BS sleeping decisions in order to maximize the quality of service while keeping the energy consumption low. Our algorithm leverages Lyapunov optimization technique, works online and achieves a close-to-optimal performance without using future information. Our simulation results show that our algorithm can effectively reduce energy consumption while guaranteeing quality of service for users.

Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Communications, ICC 2017
EditorsMerouane Debbah, David Gesbert, Abdelhamid Mellouk
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467389990
StatePublished - Jul 28 2017
Event2017 IEEE International Conference on Communications, ICC 2017 - Paris, France
Duration: May 21 2017May 25 2017

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607


Other2017 IEEE International Conference on Communications, ICC 2017

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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