scholarly journals User mobility aware task assignment for Mobile Edge Computing

2018 ◽  
Vol 85 ◽  
pp. 1-8 ◽  
Author(s):  
Zi Wang ◽  
Zhiwei Zhao ◽  
Geyong Min ◽  
Xinyuan Huang ◽  
Qiang Ni ◽  
...  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Wenchen Zhou ◽  
Weiwei Fang ◽  
Yangyang Li ◽  
Bo Yuan ◽  
Yiming Li ◽  
...  

Mobile edge computing (MEC) provides cloud-computing services for mobile devices to offload intensive computation tasks to the physically proximal MEC servers. In this paper, we consider a multiserver system where a single mobile device asks for computation offloading to multiple nearby servers. We formulate this offloading problem as the joint optimization of computation task assignment and CPU frequency scaling, in order to minimize a tradeoff between task execution time and mobile energy consumption. The resulting optimization problem is combinatorial in essence, and the optimal solution generally can only be obtained by exhaustive search with extremely high complexity. Leveraging the Markov approximation technique, we propose a light-weight algorithm that can provably converge to a bounded near-optimal solution. The simulation results show that the proposed algorithm is able to generate near-optimal solutions and outperform other benchmark algorithms.


2021 ◽  
Vol 17 (2) ◽  
pp. 155014772199340
Author(s):  
Lanlan Rui ◽  
Shuyun Wang ◽  
Zhili Wang ◽  
Ao Xiong ◽  
Huiyong Liu

Mobile edge computing is a new computing paradigm, which pushes cloud computing capabilities away from the centralized cloud to the network edge to satisfy the increasing amounts of low-latency tasks. However, challenges such as service interruption caused by user mobility occur. In order to address this problem, in this article, we first propose a multiple service placement algorithm, which initializes the placement of each service according to the user’s initial location and their service requests. Furthermore, we build a network model and propose a based on Lyapunov optimization method with long-term cost constraints. Considering the importance of user mobility, we use the Kalman filter to correct the user’s location to improve the success rate of communication between the device and the server. Compared with the traditional scheme, extensive simulation results show that the dynamic service migration strategy can effectively improve the service efficiency of mobile edge computing in the user’s mobile scene, reduce the delay of requesting terminal nodes, and reduce the service interruption caused by frequent user movement.


2019 ◽  
Vol 67 (6) ◽  
pp. 4193-4207 ◽  
Author(s):  
Hong Xing ◽  
Liang Liu ◽  
Jie Xu ◽  
Arumugam Nallanathan

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