An Energy-Efficient Opportunistic Routing Protocol Based on Trajectory Prediction for FANETs

In recent years, with the emergence of UAVs(Unmanned Aerial Vehicles) in military and civil applications, the FANETs(Flying Ad-Hoc Networks) composed of multiple UAVs has attracted extensive attention from researchers. As a new type of airborne self-organizing network, the particularity in FANETs such as time-varying network topology and dynamic link makes it difficult to maintain continuous communication when performing tasks. Therefore, it is challenging to design a routing protocol for FANETs to guarantee the quality of data transmission and make communication more effective. In this article, we propose a new opportunistic routing protocol based on trajectory prediction, named EORB-TP. To be specific, we first predict the position of nodes in three-dimensional space and solve the problem of uncertainty of node contact in opportunistic communication. Secondly, we define the node’s trajectory metric value to measure the node’s trajectory characteristics and effectively avoid the excessive consumption of edge nodes. In addition, when choosing relay nodes, an energy-saving data forwarding strategy is designed to deal with the limited energy resources and storage space of UAVs. Simulation results show that compared with the state-of-the-art protocols, our protocol can increase the delivery rate by approximately 40% at best and can reduce the delay by approximately 80%.

[1]  Liang Liu,et al.  FNTAR: A Future Network Topology-aware Routing protocol in UAV networks , 2020, 2020 IEEE Wireless Communications and Networking Conference (WCNC).

[2]  Wu Liu,et al.  Large-scale vehicle re-identification in urban surveillance videos , 2016, 2016 IEEE International Conference on Multimedia and Expo (ICME).

[3]  Vishal Sharma,et al.  DPTR: Distributed priority tree-based routing protocol for FANETs , 2018, Comput. Commun..

[4]  Xianfeng Li,et al.  LEPR: Link Stability Estimation-based Preemptive Routing protocol for Flying Ad Hoc Networks , 2017, 2017 IEEE Symposium on Computers and Communications (ISCC).

[5]  Meiyi Yang,et al.  Smart perception and autonomic optimization: A novel bio-inspired hybrid routing protocol for MANETs , 2018, Future Gener. Comput. Syst..

[6]  Young-Jun Son,et al.  Vision-Based Target Detection and Localization via a Team of Cooperative UAV and UGVs , 2016, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[7]  Pascal Lorenz,et al.  Routing in Flying Ad Hoc Networks: Survey, Constraints, and Future Challenge Perspectives , 2019, IEEE Access.

[8]  Xin Wei Evolutionary continuous optimization by Bayesian networks and Guassian mixture model , 2010, IEEE 10th INTERNATIONAL CONFERENCE ON SIGNAL PROCESSING PROCEEDINGS.

[9]  B. Muthén,et al.  Finite Mixture Modeling with Mixture Outcomes Using the EM Algorithm , 1999, Biometrics.

[10]  Mario Gerla,et al.  Satisfactory video dissemination on FANETs based on an enhanced UAV relay placement service , 2018, Ann. des Télécommunications.

[11]  Fabio Morbidi,et al.  Active Target Tracking and Cooperative Localization for Teams of Aerial Vehicles , 2013, IEEE Transactions on Control Systems Technology.

[12]  Seungmin Rho,et al.  Energy Aware Cluster-Based Routing in Flying Ad-Hoc Networks , 2018, Sensors.

[13]  Xianbin Wang,et al.  Mobility and Location-Aware Stable Clustering Scheme for UAV Networks , 2020, IEEE Access.

[14]  Shrikanth S. Narayanan,et al.  On smoothing articulatory trajectories obtained from Gaussian mixture model based acoustic-to-articulatory inversion. , 2013, The Journal of the Acoustical Society of America.

[15]  Ozgur Koray Sahingoz,et al.  Networking Models in Flying Ad-Hoc Networks (FANETs): Concepts and Challenges , 2013, Journal of Intelligent & Robotic Systems.

[16]  Xiaojiang Du,et al.  A Course-Aware Opportunistic Routing Protocol for FANETs , 2019, IEEE Access.

[17]  Ian F. Akyildiz,et al.  BorderSense: Border patrol through advanced wireless sensor networks , 2011, Ad Hoc Networks.

[18]  Changjun Jiang,et al.  Intelligent UAV Identity Authentication and Safety Supervision Based on Behavior Modeling and Prediction , 2020, IEEE Transactions on Industrial Informatics.

[19]  Dehai Zhang,et al.  TARCS: A Topology Change Aware-Based Routing Protocol Choosing Scheme of FANETs , 2019 .

[20]  Torsten Braun,et al.  Adaptive Beaconless Opportunistic Routing for Multimedia Distribution , 2015, WWIC.

[21]  Moayad Aloqaily,et al.  UAV-Assisted Vehicular Communication for Densely Crowded Environments , 2020, NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium.

[22]  Lav Gupta,et al.  Survey of Important Issues in UAV Communication Networks , 2016, IEEE Communications Surveys & Tutorials.

[23]  Alexey V. Leonov,et al.  Performance Evaluation of AODV and OLSR Routing Protocols in Relaying Networks in Organization in Mini-Uavs Based FANET: Simulation-Based Study , 2018, 2018 Dynamics of Systems, Mechanisms and Machines (Dynamics).

[24]  Nasreddine Lagraa,et al.  GeoUAVs: A new geocast routing protocol for fleet of UAVs , 2020, Comput. Commun..

[25]  Ming Zhao,et al.  Routing Algorithm Based on Trajectory Prediction in Opportunistic Networks , 2019, Inf..

[26]  Sangman Moh,et al.  Location-Aided Delay Tolerant Routing Protocol in UAV Networks for Post-Disaster Operation , 2018, IEEE Access.

[27]  Honghai Wu,et al.  Review and Comparison of Emerging Routing Protocols in Flying Ad Hoc Networks , 2020, Symmetry.

[28]  Huadong Ma,et al.  On Coverage Problems of Directional Sensor Networks , 2005, MSN.

[29]  Athanasios V. Vasilakos,et al.  A Biology-Based Algorithm to Minimal Exposure Problem of Wireless Sensor Networks , 2014, IEEE Transactions on Network and Service Management.

[30]  Robert E. Mahony,et al.  Image-Based Visual Servo Control of the Translation Kinematics of a Quadrotor Aerial Vehicle , 2009, IEEE Transactions on Robotics.

[31]  Daniel Pack,et al.  An optimal sensor management technique for Unmanned Aerial Vehicles tracking multiple mobile ground targets , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[32]  Ian F. Akyildiz,et al.  Help from the Sky: Leveraging UAVs for Disaster Management , 2017, IEEE Pervasive Computing.

[33]  Feng Jiang,et al.  Optimization of UAV Heading for the Ground-to-Air Uplink , 2011, IEEE Journal on Selected Areas in Communications.

[34]  Walid Saad,et al.  Wireless Communication Using Unmanned Aerial Vehicles (UAVs): Optimal Transport Theory for Hover Time Optimization , 2017, IEEE Transactions on Wireless Communications.

[35]  Eduardo Cerqueira,et al.  Opportunistic routing for multi-flow video dissemination over Flying Ad-Hoc Networks , 2014, Proceeding of IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks 2014.

[36]  John D. Hedengren,et al.  Evolutionary View Planning for Optimized UAV Terrain Modeling in a Simulated Environment , 2015, Remote. Sens..

[37]  Yang Yang,et al.  Opportunistic Mobility Utilization in Flying Ad-Hoc Networks: A Dynamic Matching Approach , 2019, IEEE Communications Letters.

[38]  Ouns Bouachir,et al.  Testbed of QoS Ad-Hoc Network Designed for Cooperative Multi-drone Tasks , 2019, MobiWac.

[39]  Ling Xing,et al.  Quality of Video Oriented and Multi-Meeting Based Routing Algorithm for Video Data Offloading , 2018, IEEE Access.

[40]  Juan-Carlos Cano,et al.  A Location-Aware Waypoint-Based Routing Protocol for Airborne DTNs in Search and Rescue Scenarios , 2018, Sensors.

[41]  Shaojie Tang,et al.  Recent progress in routing protocols of mobile opportunistic networks: A clear taxonomy, analysis and evaluation , 2016, J. Netw. Comput. Appl..

[42]  Liang Liu,et al.  Vbargain: A Market-Driven Quality Oriented Incentive for Mobile Video Offloading , 2019, IEEE Transactions on Mobile Computing.

[43]  Aníbal Ollero,et al.  Journal of Intelligent & Robotic Systems manuscript No. (will be inserted by the editor) An Unmanned Aircraft System for Automatic Forest Fire Monitoring and Measurement , 2022 .