UAV-Aided Data Acquisition Using Gaining-Sharing Knowledge Optimization Algorithm

被引:5
作者
Tawfik, Rania M. [1 ]
Nomer, Hazem A. A. [2 ]
Darweesh, M. Saeed [1 ]
Mohamed, Ali Wagdy [3 ,4 ]
Mostafa, Hassan [5 ,6 ]
机构
[1] Nile Univ, Wireless Intelligent Networks Ctr WINC, Sch Engn & Appl Sci, Giza 12677, Egypt
[2] Nile Univ, Sch Informat Technol & Comp Sci ITCS, Giza 12677, Egypt
[3] Cairo Univ, Fac Grad Studies Stat Res, Operat Res Dept, Giza 12613, Egypt
[4] Amer Univ Cairo, Sch Sci & Engn, Dept Math & Actuarial Sci, New Cairo, Egypt
[5] Cairo Univ, Elect & Commun Engn Dept, Giza, Egypt
[6] Univ Sci & Technol, Nanotechnol & Nanoelect Program, Zewail City Sci & Technol, Giza 12578, Egypt
来源
CMC-COMPUTERS MATERIALS & CONTINUA | 2022年 / 72卷 / 03期
关键词
NB-IoT; UAV; GSK; stop points; optimization; VEHICLE BASE STATION; RESOURCE-ALLOCATION; 3-D PLACEMENT; INTERNET; THINGS;
D O I
10.32604/cmc.2022.028234
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Unmanned Aerial Vehicles (UAVs) provide a reliable and energyefficient solution for data collection from the Narrowband Internet of Things (NB-IoT) devices. However, the UAV's deployment optimization, including locations of the UAV's stop points, is a necessity to minimize the energy consumption of the UAV and the NB-IoT devices and also to conduct the data collection efficiently. In this regard, this paper proposes Gaining-Sharing Knowledge (GSK) algorithm for optimizing the UAV's deployment. In GSK, the number of UAV's stop points in the three-dimensional space is encapsulated into a single individual with a fixed length representing an entire deployment. The superiority of using GSK in the tackled problem is verified by simulation in seven scenarios. It provides significant results in all seven scenarios compared with other four optimization algorithms used before with the same problem. Besides, the NB-IoT is proposed as the wireless communication technology between the UAV and IoT devices.
引用
收藏
页码:5999 / 6013
页数:15
相关论文
共 52 条
[1]   Salp swarm algorithm: a comprehensive survey [J].
Abualigah, Laith ;
Shehab, Mohammad ;
Alshinwan, Mohammad ;
Alabool, Hamzeh .
NEURAL COMPUTING & APPLICATIONS, 2020, 32 (15) :11195-11215
[2]   Chaotic gaining sharing knowledge-based optimization algorithm: an improved metaheuristic algorithm for feature selection [J].
Agrawal, Prachi ;
Ganesh, Talari ;
Mohamed, Ali Wagdy .
SOFT COMPUTING, 2021, 25 (14) :9505-9528
[3]   S-shaped and V-shaped gaining-sharing knowledge-based algorithm for feature selection [J].
Agrawal, Prachi ;
Ganesh, Talari ;
Oliva, Diego ;
Mohamed, Ali Wagdy .
APPLIED INTELLIGENCE, 2022, 52 (01) :81-112
[4]   Solving knapsack problems using a binary gaining sharing knowledge-based optimization algorithm [J].
Agrawal, Prachi ;
Ganesh, Talari ;
Mohamed, Ali Wagdy .
COMPLEX & INTELLIGENT SYSTEMS, 2022, 8 (01) :43-63
[5]   A novel binary gaining-sharing knowledge-based optimization algorithm for feature selection [J].
Agrawal, Prachi ;
Ganesh, Talari ;
Mohamed, Ali Wagdy .
NEURAL COMPUTING & APPLICATIONS, 2021, 33 (11) :5989-6008
[6]  
Agrawal P, 2020, 2020 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2020), P158, DOI 10.1109/ComPE49325.2020.9200089
[7]  
Al-Doori Q, 2015, COMPUT SCI ELECTR, P19, DOI 10.1109/CEEC.2015.7332693
[8]   Denial-of-Service Attack Detection over IPv6 Network Based on KNN Algorithm [J].
Alharbi, Yasser ;
Alferaidi, Ali ;
Yadav, Kusum ;
Dhiman, Gaurav ;
Kautish, Sandeep .
WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021
[9]   3-D Placement of an Unmanned Aerial Vehicle Base Station for Maximum Coverage of Users With Different QoS Requirements [J].
Alzenad, Mohamed ;
El-Keyi, Amr ;
Yanikomeroglu, Halim .
IEEE WIRELESS COMMUNICATIONS LETTERS, 2018, 7 (01) :38-41
[10]   3-D Placement of an Unmanned Aerial Vehicle Base Station (UAV-BS) for Energy-Efficient Maximal Coverage [J].
Alzenad, Mohamed ;
El-Keyi, Amr ;
Lagum, Faraj ;
Yanikomeroglu, Halim .
IEEE WIRELESS COMMUNICATIONS LETTERS, 2017, 6 (04) :434-437