论文标题
多层水下计算的环境意识AUV轨迹设计和资源管理
Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing
论文作者
论文摘要
水下事物（IOUT）被认为是海上活动的重要组成部分。鉴于IOUT设备的广阔区域分布和限制的发射功率，因此已广泛采用自动的水下车辆（AUV），用于收集和转发IOUT设备感知的数据到地表站。为了满足IOUT应用程序的各种要求，必须通过仔细利用计算机和通信以及AUVS和AUVS的存储资源以及AUVS以及IOUT设备的存储资源来构想多层水下计算（MTUC）框架。此外，为了满足IOUT设备的严格能源限制并降低MTUC框架的运营成本，制定了共同环境感知的AUV轨迹设计和资源管理问题，这是一个高维的NP-HARD问题。为了应对这一挑战，我们首先将问题转变为马尔可夫决策过程（MDP），并借助异步优势参与者-Critic（A3C）算法来解决它。我们的仿真结果证明了我们计划的优势。
The Internet of underwater things (IoUT) is envisioned to be an essential part of maritime activities. Given the IoUT devices' wide-area distribution and constrained transmit power, autonomous underwater vehicles (AUVs) have been widely adopted for collecting and forwarding the data sensed by IoUT devices to the surface-stations. In order to accommodate the diverse requirements of IoUT applications, it is imperative to conceive a multi-tier underwater computing (MTUC) framework by carefully harnessing both the computing and the communications as well as the storage resources of both the surface-station and of the AUVs as well as of the IoUT devices. Furthermore, to meet the stringent energy constraints of the IoUT devices and to reduce the operating cost of the MTUC framework, a joint environment-aware AUV trajectory design and resource management problem is formulated, which is a high-dimensional NP-hard problem. To tackle this challenge, we first transform the problem into a Markov decision process (MDP) and solve it with the aid of the asynchronous advantage actor-critic (A3C) algorithm. Our simulation results demonstrate the superiority of our scheme.
