scholarly journals Priority-Based Offloading and Caching in Mobile Edge Cloud

Author(s):  
Fernaz Narin Nur ◽  
Saiful Islam ◽  
Nazmun Nessa Moon ◽  
Asif Karim ◽  
Sami Azam ◽  
...  

Mobile Edge Computing (MEC) is relatively a novel concept in the parlance of Computational Offloading. MEC signifies the offloading of intensive computational tasks to the cloud which is generally positioned at the edge of a mobile network. Being in an embryonic stage of development, not much research has yet been done in this field despite its potential promises. However, with time the advantages are gaining growing attention and MEC is gradually taking over some of the resource-intensive functionalities of a traditional centralized cloud-based system. Another new idea called Task Caching is emerging rapidly with the offloading policy. This joint optimization idea of Task Offloading and caching is relatively a very new concept. It has been in use for reducing energy consumption and delay time for mobile edge computing. Due to the encouraging offshoots from some of the current research on the joint optimization problem, this research initiative aims to take the progress forward. The work improves upon the “prioritization of the tasks” by adopting a very practical approach discussed forward, and proposes a different way for Task Offloading and caching to the edge of the cloud, thereby bringing a significant enhancement to the QoS of MEC.

2021 ◽  
Vol 103 ◽  
pp. 107142
Author(s):  
Kai Peng ◽  
Jiangtian Nie ◽  
Neeraj Kumar ◽  
Chao Cai ◽  
Jiawen Kang ◽  
...  

2021 ◽  
Vol 13 (8) ◽  
pp. 1547
Author(s):  
Yixin He ◽  
Daosen Zhai ◽  
Fanghui Huang ◽  
Dawei Wang ◽  
Xiao Tang ◽  
...  

In this paper, we propose a mobile edge computing (MEC)-enabled unmanned aerial vehicle (UAV)-assisted vehicular ad hoc network (VANET) architecture, based on which a number of vehicles are served by UAVs equipped with computation resource. Each vehicle has to offload its computing tasks to the proper MEC server on the UAV due to the limited computation ability. To counter the problems above, we first model and analyze the transmission model and the security assurance model from the vehicle to the MEC server on UAV, and the task computation model of the local vehicle and the edge UAV. Then, the vehicle offloading problem is formulated as a multi-objective optimization problem by jointly considering the task offloading, the resource allocation, and the security assurance. For tackling this hard problem, we decouple the multi-objective optimization problem as two subproblems and propose an efficient iterative algorithm to jointly make the MEC selection decision based on the criteria of load balancing and optimize the offloading ratio and the computation resource according to the Lagrangian dual decomposition. Finally, the simulation results demonstrate that our proposed scheme achieves significant performance superiority compared with other schemes in terms of the successful task processing ratio and the task processing delay.


Author(s):  
Jia Yan ◽  
Suzhi Bi ◽  
Lingjie Duan ◽  
Ying-Jun Angela Zhang

2021 ◽  
Vol 8 (11) ◽  
pp. 9407-9421
Author(s):  
Jie Feng ◽  
Lei Liu ◽  
Qingqi Pei ◽  
Fen Hou ◽  
Tingting Yang ◽  
...  

Author(s):  
Jianshan Zhou ◽  
Daxin Tian ◽  
Zhengguo Sheng ◽  
Xuting Duan ◽  
Xuemin Shen

Author(s):  
Naouri Abdenacer ◽  
Hangxing Wu ◽  
Nouri Nabil Abdelkader ◽  
Sahraoui Dhelim ◽  
Huansheng Ning

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