Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing

Xiangwang Hou; Jingjing Wang; Tong Bai; Yansha Deng; Yong Ren; Lajos Hanzo

doi:10.1109/JSAC.2022.3227103

Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing

Xiangwang Hou, Jingjing Wang^*, Tong Bai, Yansha Deng, Yong Ren, Lajos Hanzo

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

41 Citations (Scopus)

Abstract

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.

Original language	English
Pages (from-to)	474-490
Number of pages	17
Journal	IEEE Journal on Selected Areas in Communications
Volume	41
Issue number	2
DOIs	https://doi.org/10.1109/JSAC.2022.3227103
Publication status	Published - 1 Feb 2023

Keywords

asynchronous advantage actor-critic (A3C)
autonomous underwater vehicles (AUV)
internet of underwater things (IoUT)
Multi-tier computing
resource allocation
trajectory optimization

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10.1109/JSAC.2022.3227103

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title = "Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing",

abstract = "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.",

keywords = "asynchronous advantage actor-critic (A3C), autonomous underwater vehicles (AUV), internet of underwater things (IoUT), Multi-tier computing, resource allocation, trajectory optimization",

author = "Xiangwang Hou and Jingjing Wang and Tong Bai and Yansha Deng and Yong Ren and Lajos Hanzo",

note = "Funding Information: The work of Jingjing Wang was supported in part by the National Natural Science Foundation of China under Grant 62071268 and Grant 6222101, in part by the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology under Grant 2020QNRC001, and in part by the Fundamental Research Funds for the Central Universities. The work of Tong Bai was supported in part by the National Natural Science Foundation of China under Grant 62101015. The work of Yansha Deng was supported in part by the Engineering and Physical Sciences Research Council (EPSRC), U.K., under Grant EP/W004348/1. The work of Yong Ren was supported in part by the National Natural Science Foundation of China under Grant 62127801, in part by the National Key Research and Development Program of China under Grant 2020YFD0901000, and in part by the Project 'The Verification Platform of Multi-Tier Coverage Communication Network for Oceans' of the Peng Cheng Laboratory under Grant LZC0020. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council under Project EP/W016605/1 and Project EP/P003990/1 (COALESCE) and in part by the European Research Council's Advanced Fellow Grant QuantCom under Grant 789028. Publisher Copyright: {\textcopyright} 1983-2012 IEEE.",

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N1 - Funding Information: The work of Jingjing Wang was supported in part by the National Natural Science Foundation of China under Grant 62071268 and Grant 6222101, in part by the Young Elite Scientist Sponsorship Program by the China Association for Science and Technology under Grant 2020QNRC001, and in part by the Fundamental Research Funds for the Central Universities. The work of Tong Bai was supported in part by the National Natural Science Foundation of China under Grant 62101015. The work of Yansha Deng was supported in part by the Engineering and Physical Sciences Research Council (EPSRC), U.K., under Grant EP/W004348/1. The work of Yong Ren was supported in part by the National Natural Science Foundation of China under Grant 62127801, in part by the National Key Research and Development Program of China under Grant 2020YFD0901000, and in part by the Project 'The Verification Platform of Multi-Tier Coverage Communication Network for Oceans' of the Peng Cheng Laboratory under Grant LZC0020. The work of Lajos Hanzo was supported in part by the Engineering and Physical Sciences Research Council under Project EP/W016605/1 and Project EP/P003990/1 (COALESCE) and in part by the European Research Council's Advanced Fellow Grant QuantCom under Grant 789028. Publisher Copyright: © 1983-2012 IEEE.

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N2 - 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.

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Environment-Aware AUV Trajectory Design and Resource Management for Multi-Tier Underwater Computing

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