Access selection considering mobile edge computing in ultra dense network

2017 ◽  
Author(s):  
Zhao Jiaming ◽  
Wu Wenjun ◽  
Guo Xiao ◽  
Fang Chao ◽  
Zhang Yanhua
Keyword(s):  
Edge Computing ◽  
Mobile Edge Computing ◽  
Dense Network ◽  
Access Selection ◽  
Ultra Dense Network

scholarly journals Enhancing Mobile Edge Computing with Efficient Load Balancing Using Load Estimation in Ultra-Dense Network

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3135
Author(s):  
Wen Chen ◽  
Yongqi Zhu ◽  
Jiawei Liu ◽  
Yuhu Chen
Keyword(s):  
Load Balancing ◽  
Mobile Devices ◽  
Edge Computing ◽  
Load Estimation ◽  
Mobile Edge Computing ◽  
Dense Network ◽  
Ping Pong ◽  
Load Balancing Algorithm ◽  
The Impact ◽  
Ultra Dense Network

With the exponential growth of mobile devices and the emergence of computationally intensive and delay-sensitive tasks, the enormous demand for data and computing resources has become a big challenge. Fortunately, the combination of mobile edge computing (MEC) and ultra-dense network (UDN) is considered to be an effective way to solve these challenges. Due to the highly dynamic mobility of mobile devices and the randomness of the work requests, the load imbalance between MEC servers will affect the performance of the entire network. In this paper, the software defined network (SDN) is applied to the task allocation in the MEC scenario of UDN, which is based on routing of corresponding information between MEC servers. Secondly, a new load balancing algorithm based on load estimation by user load prediction is proposed to solve the NP-hard problem in task offloading. Furthermore, a genetic algorithm (GA) is used to prove the effectiveness and rapidity of the algorithm. At present, if the load balancing algorithm only depends on the actual load of each MEC, it usually leads to ping-pong effect. It is worth mentioning that our method can effectively reduce the impact of ping-pong effect. In addition, this paper also discusses the subtask offloading problem of divisible tasks and the corresponding solutions. At last, simulation results demonstrate the efficiency of our method in balancing load among MEC servers and its ability to optimize systematic stability.

Load Balancing for Energy-Harvesting Mobile Edge Computing

2021 ◽  
Vol E104.A (1) ◽  
pp. 336-342
Author(s):  
Ping ZHAO ◽  
Jiawei TAO ◽  
Abdul RAUF ◽  
Fengde JIA ◽  
Longting XU
Keyword(s):  
Energy Harvesting ◽  
Load Balancing ◽  
Edge Computing ◽  
Mobile Edge Computing

Computation Offloading Game in Multiple UAV-Enabled Mobile Edge Computing Networks

2020 ◽  
Author(s):  
Yanling Ren ◽  
Zhibin Xie ◽  
Zhenfeng Ding ◽  
xiyuan sun ◽  
Jie Xia ◽  
...  
Keyword(s):  
Edge Computing ◽  
Computation Offloading ◽  
Mobile Edge Computing

Communication-efficient Offloading for Mobile Edge Computing in 5G Heterogeneous Networks

2020 ◽  
pp. 1-1
Author(s):  
Ping Zhou ◽  
Ke Shen ◽  
Neeraj Kumar ◽  
Yin Zhang ◽  
Mohammad Mehedi Hassan ◽  
...  
Keyword(s):  
Heterogeneous Networks ◽  
Edge Computing ◽  
Mobile Edge Computing
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