scholarly journals EMM: Energy-Aware Mobility Management for Mobile Edge Computing in Ultra Dense Networks

2017 ◽  
Vol 35 (11) ◽  
pp. 2637-2646 ◽  
Author(s):  
Yuxuan Sun ◽  
Sheng Zhou ◽  
Jie Xu
2020 ◽  
Vol 17 (12) ◽  
pp. 17-36
Author(s):  
Sha Xie ◽  
Haoran Li ◽  
Lingxiang Li ◽  
Zhi Chen ◽  
Shaoqian Li

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 184172-184182 ◽  
Author(s):  
Xin Chen ◽  
Zhiyong Liu ◽  
Ying Chen ◽  
Zhuo Li

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Bego Blanco ◽  
Ianire Taboada ◽  
Jose Oscar Fajardo ◽  
Fidel Liberal

In the context of cloud-enabled 5G radio access networks with network function virtualization capabilities, we focus on the virtual network function placement problem for a multitenant cluster of small cells that provide mobile edge computing services. Under an emerging distributed network architecture and hardware infrastructure, we employ cloud-enabled small cells that integrate microservers for virtualization execution, equipped with additional hardware appliances. We develop an energy-aware placement solution using a robust optimization approach based on service demand uncertainty in order to minimize the power consumption in the system constrained by network service latency requirements and infrastructure terms. Then, we discuss the results of the proposed placement mechanism in 5G scenarios that combine several service flavours and robust protection values. Once the impact of the service flavour and robust protection on the global power consumption of the system is analyzed, numerical results indicate that our proposal succeeds in efficiently placing the virtual network functions that compose the network services in the available hardware infrastructure while fulfilling service constraints.


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