Base station switching problem for green cellular networks with Social Spider Algorithm

James J.Q. Yu; Victor O.K. Li

doi:10.1109/CEC.2014.6900235

Base station switching problem for green cellular networks with Social Spider Algorithm

James J.Q. Yu^*
, Victor O.K. Li

^*Corresponding author for this work

The University of Hong Kong

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

16 Scopus citations

Abstract

With the recent explosion in mobile data, the energy consumption and carbon footprint of the mobile communications industry is rapidly increasing. It is critical to develop more energy-efficient systems in order to reduce the potential harmful effects to the environment. One potential strategy is to switch off some of the under-utilized base stations during off-peak hours. In this paper, we propose a binary Social Spider Algorithm to give guidelines for selecting base stations to switch off. In our implementation, we use a penalty function to formulate the problem and manage to bypass the large number of constraints in the original optimization problem. We adopt several randomly generated cellular networks for simulation and the results indicate that our algorithm can generate superior performance.

Original language	English
Title of host publication	Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	2338-2344
Number of pages	7
ISBN (Electronic)	9781479914883
DOIs	https://doi.org/10.1109/CEC.2014.6900235
State	Published - 16 Sep 2014
Externally published	Yes
Event	2014 IEEE Congress on Evolutionary Computation, CEC 2014 - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014

Publication series

Name	Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014

Conference

Conference	2014 IEEE Congress on Evolutionary Computation, CEC 2014
Country/Territory	China
City	Beijing
Period	6/07/14 → 11/07/14

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

Green cellular network
base station switching
evolutionary computation
social spider algorithm
swarm intelligence

Access to Document

10.1109/CEC.2014.6900235

Cite this

Yu, J. J. Q., & Li, V. O. K. (2014). Base station switching problem for green cellular networks with Social Spider Algorithm. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014 (pp. 2338-2344). Article 6900235 (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CEC.2014.6900235

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title = "Base station switching problem for green cellular networks with Social Spider Algorithm",

abstract = "With the recent explosion in mobile data, the energy consumption and carbon footprint of the mobile communications industry is rapidly increasing. It is critical to develop more energy-efficient systems in order to reduce the potential harmful effects to the environment. One potential strategy is to switch off some of the under-utilized base stations during off-peak hours. In this paper, we propose a binary Social Spider Algorithm to give guidelines for selecting base stations to switch off. In our implementation, we use a penalty function to formulate the problem and manage to bypass the large number of constraints in the original optimization problem. We adopt several randomly generated cellular networks for simulation and the results indicate that our algorithm can generate superior performance.",

keywords = "Green cellular network, base station switching, evolutionary computation, social spider algorithm, swarm intelligence",

author = "Yu, \{James J.Q.\} and Li, \{Victor O.K.\}",

note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE Congress on Evolutionary Computation, CEC 2014 ; Conference date: 06-07-2014 Through 11-07-2014",

year = "2014",

month = sep,

day = "16",

doi = "10.1109/CEC.2014.6900235",

language = "英语",

series = "Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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booktitle = "Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014",

address = "美国",

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Yu, JJQ & Li, VOK 2014, Base station switching problem for green cellular networks with Social Spider Algorithm. in Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014., 6900235, Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014, Institute of Electrical and Electronics Engineers Inc., pp. 2338-2344, 2014 IEEE Congress on Evolutionary Computation, CEC 2014, Beijing, China, 6/07/14. https://doi.org/10.1109/CEC.2014.6900235

Base station switching problem for green cellular networks with Social Spider Algorithm. / Yu, James J.Q.; Li, Victor O.K.
Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 2338-2344 6900235 (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Li, Victor O.K.

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N2 - With the recent explosion in mobile data, the energy consumption and carbon footprint of the mobile communications industry is rapidly increasing. It is critical to develop more energy-efficient systems in order to reduce the potential harmful effects to the environment. One potential strategy is to switch off some of the under-utilized base stations during off-peak hours. In this paper, we propose a binary Social Spider Algorithm to give guidelines for selecting base stations to switch off. In our implementation, we use a penalty function to formulate the problem and manage to bypass the large number of constraints in the original optimization problem. We adopt several randomly generated cellular networks for simulation and the results indicate that our algorithm can generate superior performance.

AB - With the recent explosion in mobile data, the energy consumption and carbon footprint of the mobile communications industry is rapidly increasing. It is critical to develop more energy-efficient systems in order to reduce the potential harmful effects to the environment. One potential strategy is to switch off some of the under-utilized base stations during off-peak hours. In this paper, we propose a binary Social Spider Algorithm to give guidelines for selecting base stations to switch off. In our implementation, we use a penalty function to formulate the problem and manage to bypass the large number of constraints in the original optimization problem. We adopt several randomly generated cellular networks for simulation and the results indicate that our algorithm can generate superior performance.

KW - Green cellular network

KW - base station switching

KW - evolutionary computation

KW - social spider algorithm

KW - swarm intelligence

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T3 - Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014

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ER -

Yu JJQ, Li VOK. Base station switching problem for green cellular networks with Social Spider Algorithm. In Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 2338-2344. 6900235. (Proceedings of the 2014 IEEE Congress on Evolutionary Computation, CEC 2014). doi: 10.1109/CEC.2014.6900235

Base station switching problem for green cellular networks with Social Spider Algorithm

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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