基于边缘计算的自适应稀疏传感网目标覆盖算法

Adaptive Sparse Sensor Network Target Coverage Algorithm Based on Edge Computing

海洋探测是海洋开发的关键,如何快速高效地实现水下目标探测是海洋探测必须解决的问题。基于此,提出了一种基于边缘计算的自适应稀疏传感网目标覆盖优化算法,以较少的传感节点高效地完成水下目标探测。首先,通过Ad Hoc移动能耗优化策略机制,添加能量因子,在节点移动过程中保护能量较低的节点,优化传感网的能量均衡性;其次,提出了一种Ad Hoc贪婪探测机制,以最小的代价实现对未知区域的探测,快速完成目标覆盖;最后,利用基于虚拟力的自适应连通机制,通过增大虚拟引力范围解决节点移动过程中的断连问题,保证了稀疏自组织网络的连通性。仿真结果表明,所提算法能够用较少数量的移动传感器提供快速、持久的目标探测覆盖,相较于对比算法性能表现更优。

Ocean exploration is the key to ocean development,and how to quickly and efficiently achieve underwater target detection is a problem that must be solved for ocean exploration.Based on this,an adaptive sparse sensing network target coverage optimization algorithm based on edge computing is proposed to efficiently accomplish underwater target detection with fewer sen-sing nodes.Firstly,the energy balance of the sensing network is optimized by adding an energy factor to protect the nodes with lower energy during the node movement through the Ad Hoc mobile energy optimization strategy mechanism.Secondly,an Ad Hoc greedy detection mechanism is proposed to achieve the detection of unknown areas with minimum cost and fast target cove-rage.Finally,using the virtual force-based adaptive connectivity mechanism,the connectivity of the sparse self-organized network is ensured by increasing the virtual gravitational range to solve the disconnection problem during the node movement.Simulation results show that the proposed algorithm is able to provide fast and durable target detection coverage with a smaller number of mobile sensors,with better performance compared to the comparison algorithms.