Energy Consumption and Delay-aware Resource Allocation Mechanism for Virtualization Cloud Radio Access Network

Ruyan WANG; Ningning XU; Dapeng WU

doi:10.11999/JEIT180063

Volume 41 Issue 1

Jan. 2019

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Ruyan WANG, Ningning XU, Dapeng WU. Energy Consumption and Delay-aware Resource Allocation Mechanism for Virtualization Cloud Radio Access Network[J]. Journal of Electronics & Information Technology, 2019, 41(1): 83-90. doi: 10.11999/JEIT180063

Citation:

Ruyan WANG, Ningning XU, Dapeng WU. Energy Consumption and Delay-aware Resource Allocation Mechanism for Virtualization Cloud Radio Access Network[J]. Journal of Electronics & Information Technology, 2019, 41(1): 83-90. doi: 10.11999/JEIT180063

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Energy Consumption and Delay-aware Resource Allocation Mechanism for Virtualization Cloud Radio Access Network

doi: 10.11999/JEIT180063

1.
School of Telecommunication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Optical Communication and Network Key Laboratory of Chongqing, Chongqing 400065, China

Funds: The National Natural Science Foundation of China (61371097, 61771082), Chongqing Funded Project of Chongqing University Innovation Team Construction (CXTDX201601020)

Received Date: 2018-01-16
Rev Recd Date: 2018-09-26

Available Online: 2018-10-19

Publish Date: 2019-01-01

Abstract

Abstract

To solve the problems of low resource utilization rate, high energy consumption and poor user service quality in the existing virtualized Cloud Radio Access Network (C-RAN), a virtual resource allocation mechanism based on energy consumption and delay is proposed. According to the network and traffic characteristics of the virtualized C-RAN, considering the resource constraints and proportional fairness, an energy consumption and delay optimization model is established. Furthermore, a heuristic algorithm is used to allocate resources for different types of virtual C-RAN and user virtual base stations to complete resource global optimization configuration. Simulation results show that the proposed resource allocation mechanism can effectively save energy by 62.99% and reduce the latency by 32.32% while improving the network resource utilization.

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References(18)

References

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