Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanne...Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.展开更多
In recent years,with the growth in Unmanned Aerial Vehicles(UAVs),UAV-based systems have become popular in both military and civil applications.In these scenarios,the lack of reliable communication infrastructure has ...In recent years,with the growth in Unmanned Aerial Vehicles(UAVs),UAV-based systems have become popular in both military and civil applications.In these scenarios,the lack of reliable communication infrastructure has motivated UAVs to establish a network as flying nodes,also known as Flying Ad Hoc Networks(FANETs).However,in FANETs,the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology,making end-to-end connections in FANETs challenging.Mobility estimation and prediction of UAVs can address the challenge mentioned above since it can provide better routing planning and improve overall FANET performance in terms of continuous service availability.We thus develop a Software Defined Network(SDN)-based heterogeneous architecture for reliable communication in FANETs.In this architecture,we apply an Extended Kalman Filter(EKF)for accurate mobility estimation and prediction of UAVs.In particular,we formulate the routing problem in SDN-based Heterogeneous FANETs as a graph decision problem.As the problem is NP-hard,we further propose a Directional Particle Swarming Optimization(DPSO)approach to solve it.The extensive simulation results demonstrate that the proposed DPSO routing can exhibit superior performance in improving the goodput,packet delivery ratio,and delay.展开更多
This paper establishes a new layered flying ad hoc networks(FANETs) system of mobile edge computing(MEC) supported by multiple UAVs,where the first layer of user UAVs can perform tasks such as area coverage, and the s...This paper establishes a new layered flying ad hoc networks(FANETs) system of mobile edge computing(MEC) supported by multiple UAVs,where the first layer of user UAVs can perform tasks such as area coverage, and the second layer of MEC UAVs are deployed as flying MEC sever for user UAVs with computing-intensive tasks. In this system, we first divide the user UAVs into multiple clusters, and transmit the tasks of the cluster members(CMs) within a cluster to its cluster head(CH). Then, we need to determine whether each CH’ tasks are executed locally or offloaded to one of the MEC UAVs for remote execution(i.e., task scheduling), and how much resources should be allocated to each CH(i.e., resource allocation), as well as the trajectories of all MEC UAVs.We formulate an optimization problem with the aim of minimizing the overall energy consumption of all user UAVs, under the constraints of task completion deadline and computing resource, which is a mixed integer non-convex problem and hard to solve. We propose an iterative algorithm by applying block coordinate descent methods. To be specific, the task scheduling between CH UAVs and MEC UAVs, computing resource allocation, and MEC UAV trajectory are alternately optimized in each iteration. For the joint task scheduling and computing resource allocation subproblem and MEC UAV trajectory subproblem, we employ branch and bound method and continuous convex approximation technique to solve them,respectively. Extensive simulation results validate the superiority of our proposed approach to several benchmarks.展开更多
Flying ad hoc networks(FANETs)present a challenging environment due to the dynamic and highly mobile nature of the network.Dynamic network topology and uncertain node mobility structure of FANETs do not aim to conside...Flying ad hoc networks(FANETs)present a challenging environment due to the dynamic and highly mobile nature of the network.Dynamic network topology and uncertain node mobility structure of FANETs do not aim to consider only one path transmission.Several different techniques are adopted to address the issues arising in FANETs,from game theory to clustering to channel estimation and other statistical schemes.These approaches mostly employ traditional concepts for problem solutions.One of the novel approaches that provide simpler solutions to more complex problems is to use biologically inspired schemes.Several Nature-inspired schemes address cooperation and alliance which can be used to ensure connectivity among network nodes.One such species that resembles the dynamicity of FANETs are Bats.In this paper,the biologically inspired metaheuristic technique of the BAT Algorithm is proposed to present a routing protocol called iBATCOOP(Improved BAT Algorithm using Cooperation technique).We opt for the design implementation of the natural posture of bats to handle the necessary flying requirements.Moreover,we envision the concept of cooperative diversity using multiple relays and present an iBAT-COOP routing protocol for FANETs.This paper employs cooperation for an optimal route selection and reflects on distance,Signal to Noise Ratio(SNR),and link conditions to an efficient level to deal with FANET’s routing.By way of simulations,the performance of iBAT-COOP protocol outperforms BAT-FANET protocol and reduces packet loss ratio,end-to-end delay,and transmission loss by 81%,21%,and 82%respectively.Furthermore,the average link duration is improved by 25%compared to the BAT-FANET protocol.展开更多
Most interesting area is the growing demand of flying-IoT mergers with smart cities.However,aerial vehicles,especially unmanned aerial vehicles(UAVs),have limited capabilities for maintaining node energy efficiency.In...Most interesting area is the growing demand of flying-IoT mergers with smart cities.However,aerial vehicles,especially unmanned aerial vehicles(UAVs),have limited capabilities for maintaining node energy efficiency.In order to communicate effectively,IoT is a key element for smart cities.While improving network performance,routing protocols can be deployed in flying-IoT to improve latency,packet drop rate,packet delivery,power utilization,and average-end-to-end delay.Furthermore,in literature,proposed techniques are verymuch complex which cannot be easily implemented in realworld applications.This issue leads to the development of lightweight energyefficient routing in flying-IoT networks.This paper addresses the energy conservation problem in flying-IoT.This paper presents a novel approach for the internet of flying vehicles using DSDV routing.ISH-DSDV gives the notion of bellman-ford algorithm consisting of routing updates,information broadcasting,and stale method.DSDV shows optimal results in comparison with other contemporary routing protocols.Nomadic mobility model is utilized in the scenario of flying networks to check the performance of routing protocols.展开更多
Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from l...Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from limited time of flight.Conventional techniques suffer from high delay,low throughput,and early node death due to aerial topology of UAV networks.To deal with these issues,this paper proposes a UAV parameter vector which considers node energy,channel state information and mobility of UAVs.By intelligently estimating the proposed parameter,the state of UAV can be predicted closely.Accordingly,efficient clustering may be achieved by using suitable metaheuristic techniques.In the current work,Elbow method has been used to determine optimal cluster count in the deployed FANET.The proposed UAV parameter vector is then integrated into two popular hybrid metaheuristic algorithms,namely,water cycle-moth flame optimization(WCMFO)and Grey Wolf-Particle Swarm optimization(GWPSO),thereby enhancing the lifespan of the system.A methodology based on the holistic approach of parameter and signal formulation,estimation model for intelligent clustering,and statistical parameters for performance analysis is carried out by the energy consumption of the network and the alive node analysis.Rigorous simulations are run to demonstrate node density variations to validate the theoretical developments for various proportions of network system sizes.The proposed method presents significant improvement over conventional stateof-the-art methods.展开更多
软件定义网络(Software Defined Network,SDN)依靠着其集中控制、可编程性和数控分离等优点,能够有效解决无人机网络(Flying Ad Hoc Network,FANET)面临的任务拓扑高度变化、网络链路连接不稳定、网络安全防护脆弱以及应用程序的异构性...软件定义网络(Software Defined Network,SDN)依靠着其集中控制、可编程性和数控分离等优点,能够有效解决无人机网络(Flying Ad Hoc Network,FANET)面临的任务拓扑高度变化、网络链路连接不稳定、网络安全防护脆弱以及应用程序的异构性等问题,极大地提升FANET的灵活性和可靠性。针对SDN架构与FANET的结合问题,描述了SDN的体系架构,并以SDN控制器部署方式为关注点分类别概括了近几年软件定义无人机网络(Software-defined Flying Ad Hoc Network,SD-FANET)的研究进展,重点阐述了结合移动边缘计算(Mobile Edge Computing,MEC)的SD-FANET研究现状,最后指出了SD-FANET的应用场景和一些具体的未来研究方向。展开更多
The ever increasing demand of adhoc networks for adaptive topology and mobility aware communication led to new paradigm of networking among Unmanned Aerial Vehicles(UAVs)known as Flying ad-hoc Networks(FANETs).Due to ...The ever increasing demand of adhoc networks for adaptive topology and mobility aware communication led to new paradigm of networking among Unmanned Aerial Vehicles(UAVs)known as Flying ad-hoc Networks(FANETs).Due to their dynamic topology,FANETs can be deployed for disaster monitoring and surveillance applications.During these operations,UAVs need to transmit different disaster data,which consists of different types of data packets.Among them there are packets which need to be transmitted urgently because of the emergency situation in disaster management.To handle this situation,we propose a methodology of disaster data classification using urgency level and based on these urgency levels,priority index is assigned to data packets.An approach of Urgency Aware Scheduling(UAS)is proposed to efficiently transmit high and low priority packets with minimum delays in transmission queue.We take into account different scenarios of UAVs for disaster management and for N number of UAVs,we propose bio-inspired mechanism using behavioral study of bird flocking for cluster formation and maintenance.Furthermore,we propose a priority based route selection methodology for data communication in FANET cluster.Simulationresults show that our proposed mechanism shows better performance in the presence of evaluation benchmarks like average delay,queuing time,forward percentage and fairness.展开更多
The routing protocols are paramount to guarantee the Quality of Service(QoS)for Flying Ad Hoc Networks(FANETs).However,they still face several challenges owing to high mobility and dynamic topology.This paper mainly f...The routing protocols are paramount to guarantee the Quality of Service(QoS)for Flying Ad Hoc Networks(FANETs).However,they still face several challenges owing to high mobility and dynamic topology.This paper mainly focuses on the adaptive routing protocol and proposes a Three Dimensional Q-Learning(3DQ)based routing protocol to guarantee the packet delivery ratio and improve the QoS.In 3DQ routing,we propose a Q-Learning based routing decision scheme,which contains a link-state prediction module and routing decision module.The link-state prediction module allows each Unmanned Aerial Vehicle(UAV)to predict the link-state of Neighboring UAVs(NUs),considering their Three Dimensional mobility and packet arrival.Then,UAV can produce routing decisions with the help of the routing decision module considering the link-state.We evaluate the various performance of 3DQ routing,and simulation results demonstrate that 3DQ can improve packet delivery ratio,goodput and delay of baseline protocol at most 71.36%,89.32%and 83.54%in FANETs over a variety of communication scenarios.展开更多
The Flying Ad-hoc Networks(FANETs)is characterized by the transition from a single large Unmanned Aerial Vehicle(UAV)to multiple small UAVs connected in an ad-hoc fashion.Since high mobility is the core feature of suc...The Flying Ad-hoc Networks(FANETs)is characterized by the transition from a single large Unmanned Aerial Vehicle(UAV)to multiple small UAVs connected in an ad-hoc fashion.Since high mobility is the core feature of such networks,they are prone to route breaks within the links.The issue of connectivity loss can be coped with,to some extent,by making use of omnidirectional antennas.Such modification,however,curtails Quality-of-Service(QoS)requirements of networks in terms of bandwidth,media access delay,coverage and others.Alternately,directional antennas have advantages over omnidirectional antennas such as improved transmission range,spatial reuse and high throughput.Nevertheless,its introduction raises location-dependent issues to the Medium Access Control(MAC)protocol.This calls for an efficient MAC protocol that can cater to new directional antenna models and,at the same time,can counter the constraints associated with the dynamic UAVs.Therefore,in this article,we consider a UAV interconnection mechanism that lets the UAVs execute the communication tasks using the directional MAC protocol.The technique is advantageous as compared to the approach of utilizing the MAC protocol using omnidirectional antennas.The scheme is being implemented as a case study for Industry 4.0 inventory and traceability applications in the warehouse.For modeling and simulation purposes,we use the Optimized Network Engineering Tool(OPNET)and aim to seek an evaluation with respect to throughput,media access delay,retransmission attempts and data dropped.The results obtained demonstrate the effectiveness of the proposed scheme.展开更多
The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data ro...The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data routing for communication between UAVs faces numerous challenges,such as low link quality,data loss,and routing path failure.This work proposes greedy perimeter stateless routing(GPSR)based design and implementation of a new adaptive communication routing protocol technique for UAVs,allowing multiple UAVs to communicate more effectively with each other in a group.Close imitation of the real environment is accomplished by considering UAVs’three-dimensional(3D)mobility in the simulations.The performance of the proposed intelligent greedy perimeter stateless routing(IGPSR)scheme has been evaluated based on end-to-end(E2E)delay,network throughput,and data loss ratio.The adapted scheme displayed on average 40%better results.The scenario has been implemented holistically on the network simulator software NS-3.展开更多
This article shows the quality of services in a wireless swarm of drones that form an ad hoc network between them Fly Ad Hoc Networks(FANET).Each drone has the ability to send and receive information(like a router);an...This article shows the quality of services in a wireless swarm of drones that form an ad hoc network between them Fly Ad Hoc Networks(FANET).Each drone has the ability to send and receive information(like a router);and can behave as a hierarchical node whit the intregration of three protocols:Multiprotocol Label Switch(MPLS),Fast Hierarchical AD Hoc Mobile(FHAM)and Internet Protocol version 6(IPv6),in conclusion MPLS+FHAM+IPv6.The metrics analyzed in the FANET are:delay,jitter,throughput,lost and sent packets/received.Testing process was carried out with swarms composed of 10,20,30 and 40 units;In this work,the stage with 40 droneswas analyzed showing registration processes,and sentmessages sequences between different drones that were part of the same swarm.A special analysis about the traffic between drones(end-to-end)was carried out,as well as the possible security flaws in each drone and the current status and future trends in real services.Regarding future trends,in a real environment,we took as a starting point,metrics results obtained in the simulation(positive according to the obtained results).These results gave us a clear vision of how the network will behave in a real environment with the aim to carry out the experiment on a physical level in the near future.This work also shows the experience quality from the service quality metrics obtained through a mathematical model.This quality of experience model will allow us to use it objectively in the agricultural sector,which is a great interest area and is where we are working with drones.Finally in this article we show our advances for a business model applied to the aforementioned agricultural sector,as well as the data analysis and services available to the end customer.These services available to the end customer have been classified into a basic,medium,advanced and plus level.展开更多
基金the National Natural Science Foundation of China(NNSFC)(Grant Nos.72001213 and 72301292)the National Social Science Fund of China(Grant No.19BGL297)the Basic Research Program of Natural Science in Shaanxi Province(Grant No.2021JQ-369).
文摘Due to the time-varying topology and possible disturbances in a conflict environment,it is still challenging to maintain the mission performance of flying Ad hoc networks(FANET),which limits the application of Unmanned Aerial Vehicle(UAV)swarms in harsh environments.This paper proposes an intelligent framework to quickly recover the cooperative coveragemission by aggregating the historical spatio-temporal network with the attention mechanism.The mission resilience metric is introduced in conjunction with connectivity and coverage status information to simplify the optimization model.A spatio-temporal node pooling method is proposed to ensure all node location features can be updated after destruction by capturing the temporal network structure.Combined with the corresponding Laplacian matrix as the hyperparameter,a recovery algorithm based on the multi-head attention graph network is designed to achieve rapid recovery.Simulation results showed that the proposed framework can facilitate rapid recovery of the connectivity and coverage more effectively compared to the existing studies.The results demonstrate that the average connectivity and coverage results is improved by 17.92%and 16.96%,respectively compared with the state-of-the-art model.Furthermore,by the ablation study,the contributions of each different improvement are compared.The proposed model can be used to support resilient network design for real-time mission execution.
文摘In recent years,with the growth in Unmanned Aerial Vehicles(UAVs),UAV-based systems have become popular in both military and civil applications.In these scenarios,the lack of reliable communication infrastructure has motivated UAVs to establish a network as flying nodes,also known as Flying Ad Hoc Networks(FANETs).However,in FANETs,the high mobility degree of flying and terrestrial users may be responsible for constant changes in the network topology,making end-to-end connections in FANETs challenging.Mobility estimation and prediction of UAVs can address the challenge mentioned above since it can provide better routing planning and improve overall FANET performance in terms of continuous service availability.We thus develop a Software Defined Network(SDN)-based heterogeneous architecture for reliable communication in FANETs.In this architecture,we apply an Extended Kalman Filter(EKF)for accurate mobility estimation and prediction of UAVs.In particular,we formulate the routing problem in SDN-based Heterogeneous FANETs as a graph decision problem.As the problem is NP-hard,we further propose a Directional Particle Swarming Optimization(DPSO)approach to solve it.The extensive simulation results demonstrate that the proposed DPSO routing can exhibit superior performance in improving the goodput,packet delivery ratio,and delay.
基金supported in part by the National Natural Science Foundation of China under Grant No.61931011in part by the Primary Research & Developement Plan of Jiangsu Province No. BE2021013-4+2 种基金in part by the National Natural Science Foundation of China under Grant No. 62072303in part by the National Postdoctoral Program for Innovative Talents of China No. BX20190202in part by the Open Project Program of the Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space No. KF20202105。
文摘This paper establishes a new layered flying ad hoc networks(FANETs) system of mobile edge computing(MEC) supported by multiple UAVs,where the first layer of user UAVs can perform tasks such as area coverage, and the second layer of MEC UAVs are deployed as flying MEC sever for user UAVs with computing-intensive tasks. In this system, we first divide the user UAVs into multiple clusters, and transmit the tasks of the cluster members(CMs) within a cluster to its cluster head(CH). Then, we need to determine whether each CH’ tasks are executed locally or offloaded to one of the MEC UAVs for remote execution(i.e., task scheduling), and how much resources should be allocated to each CH(i.e., resource allocation), as well as the trajectories of all MEC UAVs.We formulate an optimization problem with the aim of minimizing the overall energy consumption of all user UAVs, under the constraints of task completion deadline and computing resource, which is a mixed integer non-convex problem and hard to solve. We propose an iterative algorithm by applying block coordinate descent methods. To be specific, the task scheduling between CH UAVs and MEC UAVs, computing resource allocation, and MEC UAV trajectory are alternately optimized in each iteration. For the joint task scheduling and computing resource allocation subproblem and MEC UAV trajectory subproblem, we employ branch and bound method and continuous convex approximation technique to solve them,respectively. Extensive simulation results validate the superiority of our proposed approach to several benchmarks.
基金funding support for this work by the Department of Information Technology,College of Computer,Qassim University,Buraydah,Saudi Arabia.
文摘Flying ad hoc networks(FANETs)present a challenging environment due to the dynamic and highly mobile nature of the network.Dynamic network topology and uncertain node mobility structure of FANETs do not aim to consider only one path transmission.Several different techniques are adopted to address the issues arising in FANETs,from game theory to clustering to channel estimation and other statistical schemes.These approaches mostly employ traditional concepts for problem solutions.One of the novel approaches that provide simpler solutions to more complex problems is to use biologically inspired schemes.Several Nature-inspired schemes address cooperation and alliance which can be used to ensure connectivity among network nodes.One such species that resembles the dynamicity of FANETs are Bats.In this paper,the biologically inspired metaheuristic technique of the BAT Algorithm is proposed to present a routing protocol called iBATCOOP(Improved BAT Algorithm using Cooperation technique).We opt for the design implementation of the natural posture of bats to handle the necessary flying requirements.Moreover,we envision the concept of cooperative diversity using multiple relays and present an iBAT-COOP routing protocol for FANETs.This paper employs cooperation for an optimal route selection and reflects on distance,Signal to Noise Ratio(SNR),and link conditions to an efficient level to deal with FANET’s routing.By way of simulations,the performance of iBAT-COOP protocol outperforms BAT-FANET protocol and reduces packet loss ratio,end-to-end delay,and transmission loss by 81%,21%,and 82%respectively.Furthermore,the average link duration is improved by 25%compared to the BAT-FANET protocol.
基金This work was supported by the Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(Grant No.NRF-2020R1I1A3074141)the Brain Research Program through the NRF funded by the Ministry of Science,ICT and Future Planning(Grant No.NRF-2019M3C7A1020406),and“Regional Innovation Strategy(RIS)”through the NRF funded by the Ministry of Education.
文摘Most interesting area is the growing demand of flying-IoT mergers with smart cities.However,aerial vehicles,especially unmanned aerial vehicles(UAVs),have limited capabilities for maintaining node energy efficiency.In order to communicate effectively,IoT is a key element for smart cities.While improving network performance,routing protocols can be deployed in flying-IoT to improve latency,packet drop rate,packet delivery,power utilization,and average-end-to-end delay.Furthermore,in literature,proposed techniques are verymuch complex which cannot be easily implemented in realworld applications.This issue leads to the development of lightweight energyefficient routing in flying-IoT networks.This paper addresses the energy conservation problem in flying-IoT.This paper presents a novel approach for the internet of flying vehicles using DSDV routing.ISH-DSDV gives the notion of bellman-ford algorithm consisting of routing updates,information broadcasting,and stale method.DSDV shows optimal results in comparison with other contemporary routing protocols.Nomadic mobility model is utilized in the scenario of flying networks to check the performance of routing protocols.
文摘Great strides have been made to realistically deploy multiple Unmanned Aerial Vehicles(UAVs)within the commercial domain,which demands a proper coordination and reliable communication among the UAVs.UAVs suffer from limited time of flight.Conventional techniques suffer from high delay,low throughput,and early node death due to aerial topology of UAV networks.To deal with these issues,this paper proposes a UAV parameter vector which considers node energy,channel state information and mobility of UAVs.By intelligently estimating the proposed parameter,the state of UAV can be predicted closely.Accordingly,efficient clustering may be achieved by using suitable metaheuristic techniques.In the current work,Elbow method has been used to determine optimal cluster count in the deployed FANET.The proposed UAV parameter vector is then integrated into two popular hybrid metaheuristic algorithms,namely,water cycle-moth flame optimization(WCMFO)and Grey Wolf-Particle Swarm optimization(GWPSO),thereby enhancing the lifespan of the system.A methodology based on the holistic approach of parameter and signal formulation,estimation model for intelligent clustering,and statistical parameters for performance analysis is carried out by the energy consumption of the network and the alive node analysis.Rigorous simulations are run to demonstrate node density variations to validate the theoretical developments for various proportions of network system sizes.The proposed method presents significant improvement over conventional stateof-the-art methods.
文摘软件定义网络(Software Defined Network,SDN)依靠着其集中控制、可编程性和数控分离等优点,能够有效解决无人机网络(Flying Ad Hoc Network,FANET)面临的任务拓扑高度变化、网络链路连接不稳定、网络安全防护脆弱以及应用程序的异构性等问题,极大地提升FANET的灵活性和可靠性。针对SDN架构与FANET的结合问题,描述了SDN的体系架构,并以SDN控制器部署方式为关注点分类别概括了近几年软件定义无人机网络(Software-defined Flying Ad Hoc Network,SD-FANET)的研究进展,重点阐述了结合移动边缘计算(Mobile Edge Computing,MEC)的SD-FANET研究现状,最后指出了SD-FANET的应用场景和一些具体的未来研究方向。
基金supported in part by the Key Project of the National Natural Science Foundation of China under Grant 61431001in part by the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University,under Grant 2017D02+1 种基金in part by the Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education,Guilin University of Electronic Technologyin part by the Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services
文摘The ever increasing demand of adhoc networks for adaptive topology and mobility aware communication led to new paradigm of networking among Unmanned Aerial Vehicles(UAVs)known as Flying ad-hoc Networks(FANETs).Due to their dynamic topology,FANETs can be deployed for disaster monitoring and surveillance applications.During these operations,UAVs need to transmit different disaster data,which consists of different types of data packets.Among them there are packets which need to be transmitted urgently because of the emergency situation in disaster management.To handle this situation,we propose a methodology of disaster data classification using urgency level and based on these urgency levels,priority index is assigned to data packets.An approach of Urgency Aware Scheduling(UAS)is proposed to efficiently transmit high and low priority packets with minimum delays in transmission queue.We take into account different scenarios of UAVs for disaster management and for N number of UAVs,we propose bio-inspired mechanism using behavioral study of bird flocking for cluster formation and maintenance.Furthermore,we propose a priority based route selection methodology for data communication in FANET cluster.Simulationresults show that our proposed mechanism shows better performance in the presence of evaluation benchmarks like average delay,queuing time,forward percentage and fairness.
基金This work is supported in part by the National Natural Science Foundation of China under Grant No.61931011in part by the National Key Research and Development Project of China under Grant No.2018YFB1800801+2 种基金in part by the Primary Research&Development plan of Jiangsu Province under Grant BE2021013-4in part by the National Natural Science Foundation of China under Grants No.61827801 and 61631020the China Scholarship Council(CSC)Grant 202006830072.
文摘The routing protocols are paramount to guarantee the Quality of Service(QoS)for Flying Ad Hoc Networks(FANETs).However,they still face several challenges owing to high mobility and dynamic topology.This paper mainly focuses on the adaptive routing protocol and proposes a Three Dimensional Q-Learning(3DQ)based routing protocol to guarantee the packet delivery ratio and improve the QoS.In 3DQ routing,we propose a Q-Learning based routing decision scheme,which contains a link-state prediction module and routing decision module.The link-state prediction module allows each Unmanned Aerial Vehicle(UAV)to predict the link-state of Neighboring UAVs(NUs),considering their Three Dimensional mobility and packet arrival.Then,UAV can produce routing decisions with the help of the routing decision module considering the link-state.We evaluate the various performance of 3DQ routing,and simulation results demonstrate that 3DQ can improve packet delivery ratio,goodput and delay of baseline protocol at most 71.36%,89.32%and 83.54%in FANETs over a variety of communication scenarios.
文摘The Flying Ad-hoc Networks(FANETs)is characterized by the transition from a single large Unmanned Aerial Vehicle(UAV)to multiple small UAVs connected in an ad-hoc fashion.Since high mobility is the core feature of such networks,they are prone to route breaks within the links.The issue of connectivity loss can be coped with,to some extent,by making use of omnidirectional antennas.Such modification,however,curtails Quality-of-Service(QoS)requirements of networks in terms of bandwidth,media access delay,coverage and others.Alternately,directional antennas have advantages over omnidirectional antennas such as improved transmission range,spatial reuse and high throughput.Nevertheless,its introduction raises location-dependent issues to the Medium Access Control(MAC)protocol.This calls for an efficient MAC protocol that can cater to new directional antenna models and,at the same time,can counter the constraints associated with the dynamic UAVs.Therefore,in this article,we consider a UAV interconnection mechanism that lets the UAVs execute the communication tasks using the directional MAC protocol.The technique is advantageous as compared to the approach of utilizing the MAC protocol using omnidirectional antennas.The scheme is being implemented as a case study for Industry 4.0 inventory and traceability applications in the warehouse.For modeling and simulation purposes,we use the Optimized Network Engineering Tool(OPNET)and aim to seek an evaluation with respect to throughput,media access delay,retransmission attempts and data dropped.The results obtained demonstrate the effectiveness of the proposed scheme.
基金Shanghai Summit Discipline in Design,ChinaSpecial Project Funding for the Shanghai Municipal Commission of Economy and Information Civil-Military Inosculation Project,China(No.JMRH-2018-1042)。
文摘The dynamic behavior,rapid mobility,abrupt changes in network topology,and numerous other flying constraints in unmanned aerial vehicle(UAV)networks make the design of a routing protocol a challenging task.The data routing for communication between UAVs faces numerous challenges,such as low link quality,data loss,and routing path failure.This work proposes greedy perimeter stateless routing(GPSR)based design and implementation of a new adaptive communication routing protocol technique for UAVs,allowing multiple UAVs to communicate more effectively with each other in a group.Close imitation of the real environment is accomplished by considering UAVs’three-dimensional(3D)mobility in the simulations.The performance of the proposed intelligent greedy perimeter stateless routing(IGPSR)scheme has been evaluated based on end-to-end(E2E)delay,network throughput,and data loss ratio.The adapted scheme displayed on average 40%better results.The scenario has been implemented holistically on the network simulator software NS-3.
基金This research has been funded by Dirección General de Investigaciones of Universidad Santiago de Cali under Call No.01-2021.
文摘This article shows the quality of services in a wireless swarm of drones that form an ad hoc network between them Fly Ad Hoc Networks(FANET).Each drone has the ability to send and receive information(like a router);and can behave as a hierarchical node whit the intregration of three protocols:Multiprotocol Label Switch(MPLS),Fast Hierarchical AD Hoc Mobile(FHAM)and Internet Protocol version 6(IPv6),in conclusion MPLS+FHAM+IPv6.The metrics analyzed in the FANET are:delay,jitter,throughput,lost and sent packets/received.Testing process was carried out with swarms composed of 10,20,30 and 40 units;In this work,the stage with 40 droneswas analyzed showing registration processes,and sentmessages sequences between different drones that were part of the same swarm.A special analysis about the traffic between drones(end-to-end)was carried out,as well as the possible security flaws in each drone and the current status and future trends in real services.Regarding future trends,in a real environment,we took as a starting point,metrics results obtained in the simulation(positive according to the obtained results).These results gave us a clear vision of how the network will behave in a real environment with the aim to carry out the experiment on a physical level in the near future.This work also shows the experience quality from the service quality metrics obtained through a mathematical model.This quality of experience model will allow us to use it objectively in the agricultural sector,which is a great interest area and is where we are working with drones.Finally in this article we show our advances for a business model applied to the aforementioned agricultural sector,as well as the data analysis and services available to the end customer.These services available to the end customer have been classified into a basic,medium,advanced and plus level.
