An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs)
Today, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique ch...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2021-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9531630/ |
id |
doaj-36ebb3c74cab441cb9d7cf31d37c08db |
---|---|
record_format |
Article |
spelling |
doaj-36ebb3c74cab441cb9d7cf31d37c08db2021-09-27T23:00:23ZengIEEEIEEE Access2169-35362021-01-01912997713000510.1109/ACCESS.2021.31114449531630An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs)Sang-Woong Lee0https://orcid.org/0000-0001-8117-6566Saqib Ali1https://orcid.org/0000-0001-7905-7306Mohammad Sadegh Yousefpoor2Efat Yousefpoor3Pooia Lalbakhsh4https://orcid.org/0000-0001-9267-2610Danial Javaheri5https://orcid.org/0000-0002-7275-2370Amir Masoud Rahmani6Mehdi Hosseinzadeh7https://orcid.org/0000-0003-3040-1801Pattern Recognition and Machine Learning Laboratory, Gachon University, Sujeonggu, Seongnam, Republic of KoreaDepartment of Information Systems, College of Economics and Political Science, Sultan Qaboos University, Al Khoudh, Muscat, OmanDepartment of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, IranDepartment of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, IranThe College of Design and Social Context, School of Global, Urban and Social Studies, RMIT University, Melbourne, VIC, AustraliaDepartment of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, IranFuture Technology Research Center, National Yunlin University of Science and Technology, Yunlin, TaiwanPattern Recognition and Machine Learning Laboratory, Gachon University, Sujeonggu, Seongnam, Republic of KoreaToday, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique characteristics, including moving in a 3D space, high mobility, frequent topological changes, limited resources, low density of nodes, and so on, which impose various challenges when designing a proper and efficient routing scheme. In this paper, we present a fuzzy logic-based routing scheme for flying ad hoc networks. The proposed routing scheme has two phases: route discovery phase and route maintenance phase. In the first phase, we propose a technique for calculating the score of each node in the network to prevent the broadcast storm problem and control the flood of the control messages, which have been broadcast to discover a new route in the network. This score is calculated based on various parameters such as movement direction, residual energy of nodes, link quality, and node stability. Moreover, in the route selection process, we design a fuzzy system to select routes with more fitness, less delay, and fewer hops for data transfer. The second phase includes two steps: preventing route failure in order to detect and modify paths at the failure threshold, and reconstructing failed routes in order to recognize and quickly replace these routes. Finally, the proposed routing scheme is implemented in NS2 to evaluate its performance and determine its efficiency. The simulation results are compared with three routing methods, namely ECaD, LEPR, and AODV. These results show that the proposed routing method outperforms other routing schemes in terms of end to end delay, packet delivery rate, route stability, and energy consumption. However, it has slightly increased the routing overhead.https://ieeexplore.ieee.org/document/9531630/Flying ad hoc network (FANET)routingfuzzy logicunmanned aerial vehicle (UAV)artificial intelligence (AI) |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sang-Woong Lee Saqib Ali Mohammad Sadegh Yousefpoor Efat Yousefpoor Pooia Lalbakhsh Danial Javaheri Amir Masoud Rahmani Mehdi Hosseinzadeh |
spellingShingle |
Sang-Woong Lee Saqib Ali Mohammad Sadegh Yousefpoor Efat Yousefpoor Pooia Lalbakhsh Danial Javaheri Amir Masoud Rahmani Mehdi Hosseinzadeh An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) IEEE Access Flying ad hoc network (FANET) routing fuzzy logic unmanned aerial vehicle (UAV) artificial intelligence (AI) |
author_facet |
Sang-Woong Lee Saqib Ali Mohammad Sadegh Yousefpoor Efat Yousefpoor Pooia Lalbakhsh Danial Javaheri Amir Masoud Rahmani Mehdi Hosseinzadeh |
author_sort |
Sang-Woong Lee |
title |
An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) |
title_short |
An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) |
title_full |
An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) |
title_fullStr |
An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) |
title_full_unstemmed |
An Energy-Aware and Predictive Fuzzy Logic-Based Routing Scheme in Flying Ad Hoc Networks (FANETs) |
title_sort |
energy-aware and predictive fuzzy logic-based routing scheme in flying ad hoc networks (fanets) |
publisher |
IEEE |
series |
IEEE Access |
issn |
2169-3536 |
publishDate |
2021-01-01 |
description |
Today, unmanned aerial vehicles (UAVs), also known as drones, have become very popular in military applications, commercial applications, and academic research. Flying ad hoc network (FANET) is a new type of ad hoc network, which groups small drones into an ad hoc form. These networks have unique characteristics, including moving in a 3D space, high mobility, frequent topological changes, limited resources, low density of nodes, and so on, which impose various challenges when designing a proper and efficient routing scheme. In this paper, we present a fuzzy logic-based routing scheme for flying ad hoc networks. The proposed routing scheme has two phases: route discovery phase and route maintenance phase. In the first phase, we propose a technique for calculating the score of each node in the network to prevent the broadcast storm problem and control the flood of the control messages, which have been broadcast to discover a new route in the network. This score is calculated based on various parameters such as movement direction, residual energy of nodes, link quality, and node stability. Moreover, in the route selection process, we design a fuzzy system to select routes with more fitness, less delay, and fewer hops for data transfer. The second phase includes two steps: preventing route failure in order to detect and modify paths at the failure threshold, and reconstructing failed routes in order to recognize and quickly replace these routes. Finally, the proposed routing scheme is implemented in NS2 to evaluate its performance and determine its efficiency. The simulation results are compared with three routing methods, namely ECaD, LEPR, and AODV. These results show that the proposed routing method outperforms other routing schemes in terms of end to end delay, packet delivery rate, route stability, and energy consumption. However, it has slightly increased the routing overhead. |
topic |
Flying ad hoc network (FANET) routing fuzzy logic unmanned aerial vehicle (UAV) artificial intelligence (AI) |
url |
https://ieeexplore.ieee.org/document/9531630/ |
work_keys_str_mv |
AT sangwoonglee anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT saqibali anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT mohammadsadeghyousefpoor anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT efatyousefpoor anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT pooialalbakhsh anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT danialjavaheri anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT amirmasoudrahmani anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT mehdihosseinzadeh anenergyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT sangwoonglee energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT saqibali energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT mohammadsadeghyousefpoor energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT efatyousefpoor energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT pooialalbakhsh energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT danialjavaheri energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT amirmasoudrahmani energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets AT mehdihosseinzadeh energyawareandpredictivefuzzylogicbasedroutingschemeinflyingadhocnetworksfanets |
_version_ |
1716866615908237312 |