Load Balancing for Energy-Harvesting Mobile Edge Computing

Ping ZHAO; Jiawei TAO; Abdul RAUF; Fengde JIA; Longting XU

doi:10.1587/transfun.2020EAL2012

Load Balancing for Energy-Harvesting Mobile Edge Computing

Ping ZHAO, Jiawei TAO, Abdul RAUF, Fengde JIA, Longting XU

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With the development of cloud computing, the Mobile Edge Computing has emerged and attracted widespread attentions. In this paper, we focus on the load balancing in MEC with energy harvesting. We first introduce the load balancing in MEC as a problem of minimizing both the energy consumption and queue redundancy. Thereafter, we adapt such a optimization problem to the Lyapunov algorithm and solve this optimization problem. Finally, extensive simulation results validate that the obtained strategy improves the capabilities of MEC systems.

Publication: IEICE TRANSACTIONS on Fundamentals Vol.E104-A No.1 pp.336-342

Publication Date: 2021/01/01

Publicized: 2020/07/27

Online ISSN: 1745-1337

DOI: 10.1587/transfun.2020EAL2012

Type of Manuscript: LETTER

Category: Mobile Information Network and Personal Communications

Authors

Ping ZHAO
  Donghua University,Ministry of Education
Jiawei TAO
  Donghua University,Ministry of Education
Abdul RAUF
  Donghua University,Ministry of Education
Fengde JIA
  Donghua University,Ministry of Education
Longting XU
  Donghua University,Ministry of Education

Keyword

Mobile Edge Computing, energy-harvesting, load balancing, energy consumption, queue redundancy

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Ping ZHAO, Jiawei TAO, Abdul RAUF, Fengde JIA, Longting XU, "Load Balancing for Energy-Harvesting Mobile Edge Computing" in IEICE TRANSACTIONS on Fundamentals, vol. E104-A, no. 1, pp. 336-342, January 2021, doi: 10.1587/transfun.2020EAL2012.
Abstract: With the development of cloud computing, the Mobile Edge Computing has emerged and attracted widespread attentions. In this paper, we focus on the load balancing in MEC with energy harvesting. We first introduce the load balancing in MEC as a problem of minimizing both the energy consumption and queue redundancy. Thereafter, we adapt such a optimization problem to the Lyapunov algorithm and solve this optimization problem. Finally, extensive simulation results validate that the obtained strategy improves the capabilities of MEC systems.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2020EAL2012/_p

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@ARTICLE{e104-a_1_336,
author={Ping ZHAO, Jiawei TAO, Abdul RAUF, Fengde JIA, Longting XU, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Load Balancing for Energy-Harvesting Mobile Edge Computing},
year={2021},
volume={E104-A},
number={1},
pages={336-342},
abstract={With the development of cloud computing, the Mobile Edge Computing has emerged and attracted widespread attentions. In this paper, we focus on the load balancing in MEC with energy harvesting. We first introduce the load balancing in MEC as a problem of minimizing both the energy consumption and queue redundancy. Thereafter, we adapt such a optimization problem to the Lyapunov algorithm and solve this optimization problem. Finally, extensive simulation results validate that the obtained strategy improves the capabilities of MEC systems.},
keywords={},
doi={10.1587/transfun.2020EAL2012},
ISSN={1745-1337},
month={January},}

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TY - JOUR
TI - Load Balancing for Energy-Harvesting Mobile Edge Computing
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 336
EP - 342
AU - Ping ZHAO
AU - Jiawei TAO
AU - Abdul RAUF
AU - Fengde JIA
AU - Longting XU
PY - 2021
DO - 10.1587/transfun.2020EAL2012
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E104-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2021
AB - With the development of cloud computing, the Mobile Edge Computing has emerged and attracted widespread attentions. In this paper, we focus on the load balancing in MEC with energy harvesting. We first introduce the load balancing in MEC as a problem of minimizing both the energy consumption and queue redundancy. Thereafter, we adapt such a optimization problem to the Lyapunov algorithm and solve this optimization problem. Finally, extensive simulation results validate that the obtained strategy improves the capabilities of MEC systems.
ER -