TY - JOUR
T1 - Latency-Aware IoT Service Provisioning in UAV-Aided Mobile-Edge Computing Networks
AU - Zhang, Liang
AU - Ansari, Nirwan
N1 - Funding Information:
Manuscript received January 7, 2020; revised April 30, 2020; accepted June 10, 2020. Date of publication June 26, 2020; date of current version October 9, 2020. This work was supported in part by the National Science Foundation under Grant CNS-1814748. (Corresponding author: Liang Zhang.) The authors are with the Advanced Networking Laboratory, Department of Electrical and Computing Engineering, New Jersey Institute of Technology, Newark, NJ 07102 USA (e-mail: lz284@njit.edu; nirwan.ansari@njit.edu). Digital Object Identifier 10.1109/JIOT.2020.3005117
Publisher Copyright:
© 2014 IEEE.
PY - 2020/10
Y1 - 2020/10
N2 - Advances in wireless communications are empowering the emerging Internet-of-Things (IoT) applications and services with billions of connected devices. Mobile-edge computing (MEC) has been proposed to reduce the round-trip delay of these applications as IoT devices may have limited computing resources and the resource-rich mobile cloud may be far away. On the other aspect, unmanned aerial vehicles (UAVs) may potentially be employed to improve the quality of service and the channel conditions of users. We thus propose to utilize the UAV as a computing node as well as a relay node to improve the average user latency in the UAV-aided MEC (UAV-MEC) network and formulate the UAV-MEC problem with the objective to minimize the average latency of all UEs. As the UAV-MEC problem is NP-hard, we decompose it into three subproblems. We propose an approximation algorithm with low complexity to solve the first subproblem and then we obtain the optimal solutions of the remaining two subproblems, upon which another proposed approximation algorithm employs these solutions to finally solve the UAV-MEC problem. The evaluation results demonstrate that the proposed algorithm is superior to three baseline algorithms.
AB - Advances in wireless communications are empowering the emerging Internet-of-Things (IoT) applications and services with billions of connected devices. Mobile-edge computing (MEC) has been proposed to reduce the round-trip delay of these applications as IoT devices may have limited computing resources and the resource-rich mobile cloud may be far away. On the other aspect, unmanned aerial vehicles (UAVs) may potentially be employed to improve the quality of service and the channel conditions of users. We thus propose to utilize the UAV as a computing node as well as a relay node to improve the average user latency in the UAV-aided MEC (UAV-MEC) network and formulate the UAV-MEC problem with the objective to minimize the average latency of all UEs. As the UAV-MEC problem is NP-hard, we decompose it into three subproblems. We propose an approximation algorithm with low complexity to solve the first subproblem and then we obtain the optimal solutions of the remaining two subproblems, upon which another proposed approximation algorithm employs these solutions to finally solve the UAV-MEC problem. The evaluation results demonstrate that the proposed algorithm is superior to three baseline algorithms.
KW - Internet of Things (IoT)
KW - joint resource allocation
KW - latency minimization
KW - mobile-edge computing (MEC)
KW - unmanned aerial vehicles (UAV)
KW - wireless backhauling
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U2 - 10.1109/JIOT.2020.3005117
DO - 10.1109/JIOT.2020.3005117
M3 - Article
AN - SCOPUS:85092710768
SN - 2327-4662
VL - 7
SP - 10573
EP - 10580
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 10
M1 - 9126811
ER -