TY - JOUR
T1 - Maximizing Network Throughput in Heterogeneous UAV Networks
AU - Li, Shuyue
AU - Li, Jing
AU - Xiang, Chaocan
AU - Xu, Wenzheng
AU - Peng, Jian
AU - Wang, Ziming
AU - Liang, Weifa
AU - Yao, Xinwei
AU - Jia, Xiaohua
AU - Das, Sajal K.
PY - 2024/6
Y1 - 2024/6
N2 - In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on homogeneous UAVs, we consider the deployment of heterogeneous UAVs where different UAVs have different computing capacities. We study a problem of deploying K heterogeneous UAVs in the air to form a temporarily connected UAV network such that the network throughput– the number of users served by the UAVs, is maximized, subject to the constraint that the number of people served by each UAV is no greater than its service capacity. We then propose a novel O(sK−−√) -approximation algorithm for the problem, where s is a given positive integer with 1≤s≤K , e.g., s=3 . We also devise an improved heuristic, based on the approximation algorithm. We finally evaluate the performance of the proposed algorithms. Experimental results show that the numbers of users served by UAVs in the solutions delivered by the proposed algorithms are increased by 25% than state-of-the-arts.
AB - In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on homogeneous UAVs, we consider the deployment of heterogeneous UAVs where different UAVs have different computing capacities. We study a problem of deploying K heterogeneous UAVs in the air to form a temporarily connected UAV network such that the network throughput– the number of users served by the UAVs, is maximized, subject to the constraint that the number of people served by each UAV is no greater than its service capacity. We then propose a novel O(sK−−√) -approximation algorithm for the problem, where s is a given positive integer with 1≤s≤K , e.g., s=3 . We also devise an improved heuristic, based on the approximation algorithm. We finally evaluate the performance of the proposed algorithms. Experimental results show that the numbers of users served by UAVs in the solutions delivered by the proposed algorithms are increased by 25% than state-of-the-arts.
KW - approximation algorithms
KW - Approximation algorithms
KW - Autonomous aerial vehicles
KW - Base stations
KW - Computer science
KW - heterogeneous UAVs
KW - Long Term Evolution
KW - Payloads
KW - Throughput
KW - UAV communication networks
KW - UAV deployment problem
UR - http://www.scopus.com/inward/record.url?scp=85181555234&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85181555234&origin=recordpage
U2 - 10.1109/TNET.2023.3347557
DO - 10.1109/TNET.2023.3347557
M3 - RGC 21 - Publication in refereed journal
SN - 1063-6692
VL - 32
SP - 2128
EP - 2142
JO - IEEE/ACM Transactions on Networking
JF - IEEE/ACM Transactions on Networking
IS - 3
ER -