The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations.The main idea is to use heterogeneous tea...The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations.The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers,and are used in the generation of ad hoc Wireless Mesh Networks(WMN).Several fundamental problems are considered and algorithms are proposed to solve these problems.The Router Node Placement problem(RNP)and a generalization of it that takes into account additional constraints arising in actual field usage is considered first.The RNP problem tries to determine how to optimally place routers in a WMN.A new algorithm,the RRT-WMN algorithm,is proposed to solve this problem.It is based in part on a novel use of the Rapidly Exploring Random Trees(RRT)algorithm used in motion planning.A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy(CMA-ES)and Particle Swarm Optimization(PSO),shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios.The Gateway Node Placement Problem(GNP)tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service(QoS)constraints.Two alternatives are proposed for solving the combined RNP-GNP problem.The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm.The second approach,WMNbyAreaDecomposition,proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions,thus creating a number of simpler RNP problems that are then solved concurrently.Both algorithms are evaluated on real-world GIS models of different size and complexity.WMNbyAreaDecomposition is shown to outperform existing algorithms using 73%to 92%fewer router nodes while at the same time satisfying all QoS requirements.展开更多
基金Supported by the ELLIIT Network Organization for Information and Communication Technology,Swedenthe Swedish Foundation for Strategic Research SSF(Smart Systems Project RIT15-0097)+2 种基金the Wallenberg AI,Autonomous Systems and Software Program:WASP WARA-PS ProjectThe 3rd author is also supported by an RExperts Program Grant 2020A1313030098 fromthe Guangdong Department of Science and Technology,China and a Sichuan Province International Science and Technology Innovation Cooperation Project Grant 2020YFH0160.
文摘The focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations.The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers,and are used in the generation of ad hoc Wireless Mesh Networks(WMN).Several fundamental problems are considered and algorithms are proposed to solve these problems.The Router Node Placement problem(RNP)and a generalization of it that takes into account additional constraints arising in actual field usage is considered first.The RNP problem tries to determine how to optimally place routers in a WMN.A new algorithm,the RRT-WMN algorithm,is proposed to solve this problem.It is based in part on a novel use of the Rapidly Exploring Random Trees(RRT)algorithm used in motion planning.A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy(CMA-ES)and Particle Swarm Optimization(PSO),shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios.The Gateway Node Placement Problem(GNP)tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service(QoS)constraints.Two alternatives are proposed for solving the combined RNP-GNP problem.The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm.The second approach,WMNbyAreaDecomposition,proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions,thus creating a number of simpler RNP problems that are then solved concurrently.Both algorithms are evaluated on real-world GIS models of different size and complexity.WMNbyAreaDecomposition is shown to outperform existing algorithms using 73%to 92%fewer router nodes while at the same time satisfying all QoS requirements.
