城市安防场景下基于边缘计算的三维侦测路径规划

3D Detection Path Planning Based on Edge Computing for Urban Security

无人机和地面警用设施搭配可及时观测地面警情、危情,结合移动边缘计算架构,将安防应用副本和服务数据推送到临近的边缘服务器上处理,以此降低网络延迟和通信代价,提供实时安防服务。然而,为了兼顾安防侦测节点的移动性以及安防监控覆盖性和实时性的要求而部署的应用副本将带来额外的部署代价,并且会产生高昂的迁移代价。以解决此问题为出发点,聚焦城市范围内公共安防场景下的移动侦测节点路径规划问题,设计了协作式的侦测路径规划和管理架构,制定了最小化能耗的侦测节点路径规划算法,在保障安防服务低延时、全覆盖的要求下,考虑异构侦测节点间的相互协作,降低系统中侦测节点的总能耗,为智慧城市安防提供可靠高效的解决方案。此外,不同参数设置下的实验表明,所提出的模型和架构可在保证安防服务需求的基础上有效地降低节点的侦测能耗。

UAVs and ground-based police facilities can be used to observe ground alarms and dangers in a timely manner.Combined with the mobile edge computing architecture,the security application replicas and service data are pushed to the adjacent edge servers for processing,thereby reducing network latency and communication costs,and providing real-time security services.However,a replica of the application deployed to balance the mobility of the security detection node with the security monitoring coverage and real-time requirements will incur additional deployment costs and high migration costs.Motivated by this problem,this paper focuses on the path planning problem of mobile detection nodes in the public security scenario within the city.A collaborative detection path planning and management architecture are designed,along with a detection node path planning algorithm to minimize the energy consumption in detection.The algorithm considers the mutual cooperation of heterogeneous detection nodes under the requirement of low latency and full coverage of urban regions,reduces the total energy consumption of detecting nodes in the system,and provides a reliable and efficient solution for smart city security.In addition,experiments with different parameter settings show that the proposed model and architecture can effectively reduce the node's detection energy consumption while guarantee the requirements of security service.