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Lifesaving with RescueChain: Energy-Efficient and Partition-Tolerant Blockchain Based Secure Information Sharing for UAV-Aided Disaster Rescue

机译:使用Rescuechain的救生:节能和分区宽容的基于无人机援助灾难救援的安全信息共享

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Unmanned aerial vehicles (UAVs) have brought numerous potentials to establish flexible and reliable emergency networks in disaster areas when terrestrial communication infrastructures go down. Nevertheless, potential security threats may occur on UAVs during data transmissions due to the untrustful environment and open-access UAV networking. Moreover, UAVs typically have limited battery and computation capacity, making them unaffordable to execute heavy security provisioning operations when carrying out complicated rescue tasks. In this paper, we develop RescueChain, a secure and efficient information sharing scheme for UAV-aided disaster rescue. Specifically, we first implement a lightweight blockchain-based framework to safeguard data sharing under disasters and immutably trace misbehaving entities. A reputation-based consensus protocol is devised to adapt the weakly connected environment with improved consensus efficiency and promoted UAVs’ honest behaviors. Furthermore, we introduce a novel vehicular fog computing based off-chain mechanism by leveraging ground vehicles as moving fog nodes to offload UAVs’ heavy data processing and storage tasks. To optimally stimulate vehicles to share their idle computing resources, we also design a two-layer reinforcement learning based incentive algorithm for UAVs and ground vehicles in the highly dynamic networks. Simulation results show that RescueChain can effectively accelerate consensus process, enhance user payoffs, and reduce delivery latency, compared with representative existing approaches.
机译:无人驾驶飞行器(UAV)已经带来了无数的潜力时,地面通信基础设施再往建立灾区灵活和可靠的应急网络。然而,可以在过程中数据传输的无人机出现由于untrustful环境和开放式接入网络的无人机潜在的安全威胁。此外,无人机通常具有有限的电池和计算能力,使他们无法负担执行复杂的救援任务时执行重安全置备操作。在本文中,我们开发RescueChain,无人机辅助抗灾抢险安全,高效的信息共享机制。具体而言,我们首先实现一个轻量级的基于blockchain的框架,以保障数据共享灾害下不可改变跟踪行为不端的实体。基于信誉的一致性协议被设计为适应具有改进的共识效率和促进无人机诚实行为弱连接的环境。此外,我们介绍一种新颖的车辆用雾通过利用地面车辆移动雾节点卸载无人机重的数据处理和存储任务计算基于截止链机构。为了最大限度促进车辆分享他们的闲置计算资源,我们还设计了双层强化学习在高度动态的网络,无人机和地面车辆以激励为基础的算法。仿真结果表明,RescueChain有效地促进了达成共识的过程,增强用户的回报,并降低传输延迟,与代表现有的方法相比。

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