TY - JOUR
T1 - Number and Operation Time Minimization for Multi-UAV Enabled Data Collection System with Time Windows
AU - Shen, Shuai
AU - Yang, Kun
AU - Wang, Kezhi
AU - Zhang, Guopeng
AU - Mei, Haibo
N1 - Funding information:
This work was supported in part by the Natural Science Foundation of China under Grant No. 61620106011, U1705263 and 61871076, and in part by the National Natural Science Foundation of China under Grant No. 61971421.
PY - 2022/6/15
Y1 - 2022/6/15
N2 - In this paper, we investigate multiple unmanned aerial vehicles (UAVs) enabled data collection system in Internet of Things (IoT) networks with time windows, where multiple rotary-wing UAVs are dispatched to collect data from time constrained terrestrial IoT devices. We aim to jointly minimize the number and the total operation time of UAVs by optimizing the UAV trajectory and hovering location. To this end, an optimization problem is formulated considering the energy budget and cache capacity of UAVs as well as the data transmission constraint of IoT devices. To tackle this mix-integer non-convex problem, we decompose the problem into two subproblems: UAV trajectory and hovering location optimization problems. To solve the first subproblem, an modified ant colony optimization (MACO) algorithm is proposed. For the second subproblem, the successive convex approximation (SCA) technique is applied. Then, an overall algorithm, termed MACO-based algorithm, is given by leveraging MACO algorithm and SCA technique. Simulation results demonstrate the superiority of the proposed algorithm.
AB - In this paper, we investigate multiple unmanned aerial vehicles (UAVs) enabled data collection system in Internet of Things (IoT) networks with time windows, where multiple rotary-wing UAVs are dispatched to collect data from time constrained terrestrial IoT devices. We aim to jointly minimize the number and the total operation time of UAVs by optimizing the UAV trajectory and hovering location. To this end, an optimization problem is formulated considering the energy budget and cache capacity of UAVs as well as the data transmission constraint of IoT devices. To tackle this mix-integer non-convex problem, we decompose the problem into two subproblems: UAV trajectory and hovering location optimization problems. To solve the first subproblem, an modified ant colony optimization (MACO) algorithm is proposed. For the second subproblem, the successive convex approximation (SCA) technique is applied. Then, an overall algorithm, termed MACO-based algorithm, is given by leveraging MACO algorithm and SCA technique. Simulation results demonstrate the superiority of the proposed algorithm.
KW - Costs
KW - Data collection
KW - Data communication
KW - Energy consumption
KW - Internet of Things
KW - Time window
KW - Trajectory
KW - UAV trajectory
KW - Unmanned aerial vehicles
KW - location optimization
KW - multi-UAV enabled system.
UR - http://www.scopus.com/inward/record.url?scp=85118238480&partnerID=8YFLogxK
U2 - 10.1109/JIOT.2021.3121511
DO - 10.1109/JIOT.2021.3121511
M3 - Article
SN - 2327-4662
VL - 9
SP - 10149
EP - 10161
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 12
ER -