Power-delay trade-off for heterogenous cloud enabled multi-UAV systems
Power-delay trade-off for heterogenous cloud enabled multi-UAV systems
Unmanned aerial vehicles (UAVs) have been widely used in a range of compelling applications. However, some of them are incompetent in tackling with computation-intensive tasks due to limited processing capability and battery life. In this paper, we combine the mobile edge computing and traditional cloud computing techniques for offloading the tasks from multi-UAV systems. Specifically, we jointly optimize the task scheduling and resource allocation in the heterogeneous cloud architecture, where we strike a power-delay trade-off of the system relying on the queue theory and Lyapunov optimization, followed by its optimal strategy analysis in each time slot. Moreover, we conceive an iterative algorithm with a closed-form solution at each iteration round in order to reduce the computational complexity. Finally, numerical results demonstrate both the feasibility and effectiveness of our proposed scheme. This paper validates that the heterogeneous cloud structure can be the beneficial for improving quality-of-service performance of multi-UAV systems.
1-6
Duan, Ruiyang
aae4c9a0-2183-4eee-9c91-7e4b31e437cf
Wang, Jingjing
0b73e219-9dd7-44ec-a260-a53ee004746f
Du, Jun
f0be0d46-1209-4be7-9b47-02bc62ca1186
Jiang, Chunxiao
16bad068-43b1-41d4-9f6b-211acdb1ae52
Bai, Tong
15e00a16-2ade-4fdb-a4d9-a490a526669a
Ren, Yong
ad146a10-75d8-401c-911b-fd4dcc44eb12
15 July 2019
Duan, Ruiyang
aae4c9a0-2183-4eee-9c91-7e4b31e437cf
Wang, Jingjing
0b73e219-9dd7-44ec-a260-a53ee004746f
Du, Jun
f0be0d46-1209-4be7-9b47-02bc62ca1186
Jiang, Chunxiao
16bad068-43b1-41d4-9f6b-211acdb1ae52
Bai, Tong
15e00a16-2ade-4fdb-a4d9-a490a526669a
Ren, Yong
ad146a10-75d8-401c-911b-fd4dcc44eb12
Duan, Ruiyang, Wang, Jingjing, Du, Jun, Jiang, Chunxiao, Bai, Tong and Ren, Yong
(2019)
Power-delay trade-off for heterogenous cloud enabled multi-UAV systems.
In 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings.
vol. 2019-May,
IEEE.
.
(doi:10.1109/ICC.2019.8761377).
Record type:
Conference or Workshop Item
(Paper)
Abstract
Unmanned aerial vehicles (UAVs) have been widely used in a range of compelling applications. However, some of them are incompetent in tackling with computation-intensive tasks due to limited processing capability and battery life. In this paper, we combine the mobile edge computing and traditional cloud computing techniques for offloading the tasks from multi-UAV systems. Specifically, we jointly optimize the task scheduling and resource allocation in the heterogeneous cloud architecture, where we strike a power-delay trade-off of the system relying on the queue theory and Lyapunov optimization, followed by its optimal strategy analysis in each time slot. Moreover, we conceive an iterative algorithm with a closed-form solution at each iteration round in order to reduce the computational complexity. Finally, numerical results demonstrate both the feasibility and effectiveness of our proposed scheme. This paper validates that the heterogeneous cloud structure can be the beneficial for improving quality-of-service performance of multi-UAV systems.
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e-pub ahead of print date: 20 May 2019
Published date: 15 July 2019
Venue - Dates:
2019 IEEE International Conference on Communications, ICC 2019, , Shanghai, China, 2019-05-20 - 2019-05-24
Identifiers
Local EPrints ID: 433759
URI: http://eprints.soton.ac.uk/id/eprint/433759
PURE UUID: 12c8ff75-87ba-48ef-936b-2f0dabd994c2
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Date deposited: 03 Sep 2019 16:30
Last modified: 17 Mar 2024 12:34
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Contributors
Author:
Ruiyang Duan
Author:
Jingjing Wang
Author:
Jun Du
Author:
Chunxiao Jiang
Author:
Tong Bai
Author:
Yong Ren
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