Tang, Qiang and Chang, Lu and Yang, Kun and Wang, Kezhi and Wang, Jin and Sharma, Pradip Kumar (2020) Task number maximization offloading strategy seamlessly adapted to UAV scenario. Computer Communications, 151. pp. 19-30. DOI https://doi.org/10.1016/j.comcom.2019.12.018
Tang, Qiang and Chang, Lu and Yang, Kun and Wang, Kezhi and Wang, Jin and Sharma, Pradip Kumar (2020) Task number maximization offloading strategy seamlessly adapted to UAV scenario. Computer Communications, 151. pp. 19-30. DOI https://doi.org/10.1016/j.comcom.2019.12.018
Tang, Qiang and Chang, Lu and Yang, Kun and Wang, Kezhi and Wang, Jin and Sharma, Pradip Kumar (2020) Task number maximization offloading strategy seamlessly adapted to UAV scenario. Computer Communications, 151. pp. 19-30. DOI https://doi.org/10.1016/j.comcom.2019.12.018
Abstract
Mobile edge computing (MEC) has been proposed in recent years to process resource-intensive and delay-sensitive applications at the edge of mobile networks, which can break the hardware limitations and resource constraints at user equipment (UE). In order to fully use the MEC server resource, how to maximize the number of offloaded tasks is meaningful especially for crowded place or disaster area. In this paper, an optimal partial offloading scheme POSMU (Partial Offloading Strategy Maximizing the User task number) is proposed to obtain the optimal offloading ratio, local computing frequency, transmission power and MEC server computing frequency for each UE. The problem is formulated as a mixed integer nonlinear programming problem (MINLP), which is NP-hard and challenging to solve. As such, we convert the problem into multiple nonlinear programming problems (NLPs) and propose an efficient algorithm to solve them by applying the block coordinate descent (BCD) as well as convex optimization techniques. Besides, we can seamlessly apply POSMU to UAV (Unmanned Aerial Vehicle) enabled MEC system by analyzing the 3D communication model. The optimality of POSMU is illustrated in numerical results, and POSMU can approximately maximize the number of offloaded tasks compared to other schemes.
Item Type: | Article |
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Uncontrolled Keywords: | Offloaded task number maximization; Partial offloading; Unmanned aerial vehicle; Mobile edge computing |
Divisions: | Faculty of Science and Health Faculty of Science and Health > Computer Science and Electronic Engineering, School of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 20 Dec 2019 09:13 |
Last Modified: | 30 Oct 2024 16:23 |
URI: | http://repository.essex.ac.uk/id/eprint/26311 |
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