TY - GEN
T1 - Multi-UAV Deployment for MEC Enhanced IoT Networks
AU - Yang, Lei
AU - Yao, Haipeng
AU - Zhang, Xing
AU - Wang, Jingjing
AU - Liu, Yunjie
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/8/9
Y1 - 2020/8/9
N2 - Unmanned aerial vehicles (UAVs) are already widely used to provide both relay services and enhanced information coverage to the terrestrial Internet of Things (IoT) networks. IoT devices may not be able to handle heavy computing tasks due to their severely limited processing capability. In this paper, a multi-UAV deployment for mobile edge computing (MEC) enhanced IoT architecture is designed, where multiple UAVs are endowed with computing offloading services for ground IoT devices with limited local processing capabilities. In order to balance the load of UAVs, this paper proposes a multi-UAV deployment mechanism which is based on the difference evolution (DE) algorithm. Meanwhile, the access problem for IoT nodes is formulated as a generalized assignment problem (GAP), and then an approximate optimal solution scheme is used to solve the problem. Based on this, we realize the load balancing of multiple UAVs, guarantee the constraint of coverage range and meet the quality of service (QoS) of MEC networks. Finally, sufficient simulations prove the effectiveness of our proposed multi-UAV deployment algorithm.
AB - Unmanned aerial vehicles (UAVs) are already widely used to provide both relay services and enhanced information coverage to the terrestrial Internet of Things (IoT) networks. IoT devices may not be able to handle heavy computing tasks due to their severely limited processing capability. In this paper, a multi-UAV deployment for mobile edge computing (MEC) enhanced IoT architecture is designed, where multiple UAVs are endowed with computing offloading services for ground IoT devices with limited local processing capabilities. In order to balance the load of UAVs, this paper proposes a multi-UAV deployment mechanism which is based on the difference evolution (DE) algorithm. Meanwhile, the access problem for IoT nodes is formulated as a generalized assignment problem (GAP), and then an approximate optimal solution scheme is used to solve the problem. Based on this, we realize the load balancing of multiple UAVs, guarantee the constraint of coverage range and meet the quality of service (QoS) of MEC networks. Finally, sufficient simulations prove the effectiveness of our proposed multi-UAV deployment algorithm.
KW - mobile edge computing
KW - multi-UAV deployment
KW - unmanned aerial vehicles
UR - https://www.scopus.com/pages/publications/85097550034
U2 - 10.1109/ICCC49849.2020.9238870
DO - 10.1109/ICCC49849.2020.9238870
M3 - 会议稿件
AN - SCOPUS:85097550034
T3 - 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020
SP - 436
EP - 441
BT - 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE/CIC International Conference on Communications in China, ICCC 2020
Y2 - 9 August 2020 through 11 August 2020
ER -