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Author:

Jiaming, Zhao (Jiaming, Zhao.) | Wenjun, Wu (Wenjun, Wu.) | Xiao, Guo (Xiao, Guo.) | Chao, Fang (Chao, Fang.) | Yanhua, Zhang (Yanhua, Zhang.) (Scholars:张延华)

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EI Scopus

Abstract:

Nowadays, wireless communications are entering the 5G era, in which Mobile Edge Computing (MEC) and Ultra Dense Network (UDN) architecture are the two core technologies. In UDN architecture, deploying MEC servers at both macro eNodeB and small eNodeB can effectively reduce delay and energy consumption, and improve the user's Quality of Experience (QoE). However, the access selection is challenging due to the dense allocation of small eNodeBs. In this paper, we propose a user access selection algorithm considering MEC in UDN. A QoE-aware cost function related to energy consumption and service delay is adopted as the performance metric. The energy consumption is calculated as the uplink transmission power of User Equipment (UE), and the service delay is counted as the sum of the transmission delay from UE to the MEC server and the processing delay of user services at the MEC server. This method is compared with the traditional optimal channel quality access method. Numerical results show that the proposed method can effectively reduce the delay and energy consumption, and thus, improve the QoE of users. © 2017 IEEE.

Keyword:

Cost functions 5G mobile communication systems User experience Network architecture Quality of service Edge computing Energy utilization Green computing Numerical methods

Author Community:

  • [ 1 ] [Jiaming, Zhao]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 2 ] [Jiaming, Zhao]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 3 ] [Wenjun, Wu]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 4 ] [Wenjun, Wu]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 5 ] [Xiao, Guo]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 6 ] [Xiao, Guo]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 7 ] [Chao, Fang]Beijing Advanced Innovation Center for Future Internet Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 8 ] [Chao, Fang]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China
  • [ 9 ] [Yanhua, Zhang]Beijing Laboratory of Advanced Information Networks, Beijing University of Technology, Beijing; 100124, China
  • [ 10 ] [Yanhua, Zhang]Faculty of Information Technology, Beijing University of Technology, Beijing; 100124, China

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Source :

Year: 2017

Volume: 2018-January

Page: 433-437

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 4

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 5

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