4.7 Article

Deep Reinforcement Learning Based Computation Offloading and Trajectory Planning for Multi-UAV Cooperative Target Search

Related references

Note: Only part of the references are listed.
Article Computer Science, Information Systems

Task Offloading Optimization for UAV-Assisted Fog-Enabled Internet of Things Networks

Xiaoge Huang et al.

Summary: This article investigates UAVs-assisted fog-enabled IoT network, where UAVs equipped with computing capabilities offer task offloading opportunities to IoT devices. By jointly optimizing UAV trajectory, transmission power, and computation offload radios, while satisfying Quality-of-Service requirements, the total network overhead can be minimized.

IEEE INTERNET OF THINGS JOURNAL (2022)

Editorial Material Chemistry, Analytical

Edge-Computing-Based Intelligent IoT: Architectures, Algorithms and Applications

Xiao Liu et al.

SENSORS (2022)

Article Engineering, Electrical & Electronic

Multi-Agent Deep Reinforcement Learning for Task Offloading in UAV-Assisted Mobile Edge Computing

Nan Zhao et al.

Summary: This paper investigates a collaborative mobile edge computing system with multiple UAVs and multiple edge clouds. The task offloading issue is addressed by jointly designing the trajectories, computation task allocation, and communication resource management of UAVs, aiming to minimize the sum of execution delays and energy consumptions.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2022)

Article Computer Science, Information Systems

Autonomous Cooperative Search Model for Multi-UAV With Limited Communication Network

Bowen Fei et al.

Summary: This article focuses on improving the cooperative search capability of multi-UAVs in an uncertain communication environment. By designing a local communication network, optimizing the function, and applying an improved sparrow search algorithm, real-time control and information sharing are achieved during the search process. Experimental results show that this method has high accuracy, stability, and convergence speed.

IEEE INTERNET OF THINGS JOURNAL (2022)

Article Computer Science, Hardware & Architecture

Joint Computation Offloading and Trajectory Design for Aerial Computing

Shangwei Zhang et al.

Summary: Multiple drones are used for efficient multi-modal multi-task processes, proposing an aerial computing framework that integrates air-ground services to provide edge computing, achieving better performance in terms of average task completion time.

IEEE WIRELESS COMMUNICATIONS (2021)

Article Engineering, Aerospace

Dynamic Discrete Pigeon-Inspired Optimization for Multi-UAV Cooperative Search-Attack Mission Planning

Haibin Duan et al.

Summary: This article proposes a dynamic discrete pigeon-inspired optimization algorithm for cooperative search-attack mission planning for multiple UAVs. It uses a solution acceptance strategy to avoid frequent task switching, and designs a reasonable objective function by constructing probability maps and employing a Sigmoid model for target allocation. Numerical experiments prove the feasibility of the proposed methods for multiple UAVs in different scenarios.

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS (2021)

Article Engineering, Civil

Vehicle Assisted Computing Offloading for Unmanned Aerial Vehicles in Smart City

Minghui Dai et al.

Summary: This article proposes a vehicle-assisted computing offloading architecture for UAVs in smart city to improve offloading efficiency. The model determines offloading strategy, a matching scheme selects optimal vehicles, and a bargaining game models the transaction process for computing data. An offloading algorithm is proposed to obtain the optimal strategy, and simulations demonstrate significant resource savings and improved utilities of UAVs and vehicles.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)

Article Engineering, Electrical & Electronic

Optimal Edge Computing for Infrastructure-Assisted UAV Systems

Davide Callegaro et al.

Summary: Unmanned Aerial Vehicles (UAV) in urban environments can enhance their autonomous capabilities by leveraging the surrounding Internet of Things infrastructure, but the complexity of urban topology and resource competition may affect task offloading performance. This paper proposes a framework that uses Dynamic Programming and Deep Reinforcement learning to solve optimal task offloading decisions based on network and computation load parameters.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

Article Computer Science, Information Systems

Autonomous UAV Trajectory for Localizing Ground Objects: A Reinforcement Learning Approach

Dariush Ebrahimi et al.

Summary: This study proposes a novel framework based on reinforcement learning for UAVs to autonomously improve object localization accuracy by minimizing location errors in the shortest time and path length. The framework considers detailed UAV to ground channel characteristics and energy consumption, showcasing superior results over existing methods in reducing localization error.

IEEE TRANSACTIONS ON MOBILE COMPUTING (2021)

Article Computer Science, Theory & Methods

Distributed and Collective Deep Reinforcement Learning for Computation Offloading: A Practical Perspective

Xiaoyu Qiu et al.

Summary: DC-DRL is a distributed and collective DRL algorithm proposed to address the gap in deploying real DRL applications in MEC. By assimilating knowledge from multiple MEC environments and using adaptive n-step learning, DC-DRL effectively increases data diversity, reduces exploration costs, and maximizes the utilization of multiple environments to prevent premature convergence. Evaluation results show a significant reduction in exploration costs and final system costs compared to baselines.

IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS (2021)

Article Engineering, Electrical & Electronic

Joint Mobility, Communication and Computation Optimization for UAVs in Air-Ground Cooperative Networks

Jianshan Zhou et al.

Summary: The paper investigates a UAV-oriented computation offloading system aiming to maximize the energy efficiency of UAV. By jointly considering UAV's mobility, A2G communication, and computation dynamics, a new solution method is proposed to address the coupled complexity and non-convexity issues. Extensive simulations demonstrate the effectiveness of the proposed method in terms of constraint satisfaction and convergence speed, outperforming other benchmark methods in terms of global energy efficiency.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

Article Automation & Control Systems

Effectiveness of a Camera as a UAV Mounted Search Sensor for Target Detection: An Experimental Investigation

Jeane Marina D'Souza et al.

Summary: This paper focuses on the problem of autonomous search using UAVs equipped with downward-facing cameras, with experiments conducted to obtain a search effectiveness model in a laboratory environment.

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS (2021)

Article Automation & Control Systems

Learning-Based Resource Allocation Strategy for Industrial IoT in UAV-Enabled MEC Systems

Lu Sun et al.

Summary: This article introduces a system architecture based on UAV and IIoT, with an optimal resource allocation strategy achieved through cooperative particle swarm optimization algorithm, minimizing the maximum response time of forest fire monitoring.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2021)

Article Engineering, Electrical & Electronic

Self-Learning Based Computation Offloading for Internet of Vehicles: Model and Algorithm

Quyuan Luo et al.

Summary: In this paper, a self-learning based distributed computation offloading scheme for IoV is proposed, establishing a game-theoretic model for optimal offloading decision-making. Through extensive simulations, the scheme outperforms counterparts and achieves significant improvements in time and message overhead.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2021)

Article Engineering, Electrical & Electronic

Joint Computation Offloading and Trajectory Planning for UAV-Assisted Edge Computing

Chao Sun et al.

Summary: This paper presents a new UAV-assisted edge computing framework that optimizes trajectory, CPU frequency, and offloading schedule to minimize energy consumption. The algorithms can achieve both global optimal linear trajectory and local optimum satisfying the Karush-Kuhn-Tucker conditions. The underlying patterns for optimal CPU frequency and offloading schedule are revealed through analysis of KKT conditions.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2021)

Article Telecommunications

Trajectory Optimization for UAV Emergency Communication With Limited User Equipment Energy: A Safe-DQN Approach

Tiankui Zhang et al.

Summary: The article investigates UAV-based emergency communication networks, optimizing UAV trajectory design to maximize uplink throughput. The algorithm converges quickly and performs well in terms of uplink throughput and UE energy efficiency, achieving a good balance.

IEEE TRANSACTIONS ON GREEN COMMUNICATIONS AND NETWORKING (2021)

Article Engineering, Electrical & Electronic

Sustainable Task Offloading in UAV Networks via Multi-Agent Reinforcement Learning

Alessio Sacco et al.

Summary: The recent growth of IoT devices and edge computing has created many new opportunities for applications, with a special focus on Unmanned Aerial Vehicles (UAVs) for surveillance and environmental monitoring. This paper introduces a distributed architecture leveraging Multi-Agent Reinforcement Learning (MARL) to dynamically offload tasks from UAVs to the edge cloud, aiming to minimize latency and energy usage. Results confirm the effectiveness of this distributed approach in achieving performance targets.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

Article Engineering, Electrical & Electronic

Learning-Based Computation Offloading Approaches in UAVs-Assisted Edge Computing

Shichao Zhu et al.

Summary: This paper proposes a UAVs-assisted computation offloading paradigm, modeling the problem of average mission response time minimization as a Markov decision process and applying multi-agent reinforcement learning algorithms to determine the target helper and bandwidth allocation. The proposed MARL-based approaches demonstrate desirable convergence properties and outperform benchmark approaches by significantly reducing average mission response time.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2021)

Article Computer Science, Information Systems

Resource Scheduling in Edge Computing: A Survey

Quyuan Luo et al.

Summary: With the increasing demand for data communications and computing, edge computing has emerged as a paradigm shift by providing powerful communication, storage, networking, and computing capacity closer to users. Resource scheduling is crucial for the success of edge computing systems, attracting growing research interest. Current research focuses on various resource scheduling techniques and application scenarios.

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (2021)

Article Engineering, Electrical & Electronic

Computation-Efficient Offloading and Trajectory Scheduling for Multi-UAV Assisted Mobile Edge Computing

Jiao Zhang et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

Article Engineering, Electrical & Electronic

Online Task Scheduling and Resource Allocation for Intelligent NOMA-Based Industrial Internet of Things

Kunlun Wang et al.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2020)

Article Engineering, Electrical & Electronic

Response Delay Optimization in Mobile Edge Computing Enabled UAV Swarm

Qixun Zhang et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2020)

Article Computer Science, Information Systems

UAV-Assisted Wireless Powered Cooperative Mobile Edge Computing: Joint Offloading, CPU Control, and Trajectory Optimization

Yuan Liu et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Engineering, Electrical & Electronic

Immune genetic algorithm based multi-UAV cooperative target search with event -triggered mechanism

Zhenwen Zhou et al.

PHYSICAL COMMUNICATION (2020)

Proceedings Paper Computer Science, Artificial Intelligence

Energy-Efficient Video Streaming in UAV-Enabled Wireless Networks: A Safe-DQN Approach

Qian Zhang et al.

2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) (2020)

Article Computer Science, Information Systems

Collaborative Data Scheduling for Vehicular Edge Computing via Deep Reinforcement Learning

Quyuan Luo et al.

IEEE INTERNET OF THINGS JOURNAL (2020)

Article Telecommunications

Task Offloading in UAV-Aided Edge Computing: Bit Allocation and Trajectory Optimization

Jingyu Xiong et al.

IEEE COMMUNICATIONS LETTERS (2019)

Article Computer Science, Hardware & Architecture

When UAV Swarm Meets Edge-Cloud Computing: The QoS Perspective

Wuhui Chen et al.

IEEE NETWORK (2019)

Article Computer Science, Information Systems

Stochastic Computation Offloading and Trajectory Scheduling for UAV-Assisted Mobile Edge Computing

Jiao Zhang et al.

IEEE INTERNET OF THINGS JOURNAL (2019)

Article Engineering, Electrical & Electronic

Energy-Efficient Computation Offloading for Secure UAV-Edge-Computing Systems

Tong Bai et al.

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY (2019)

Article Engineering, Electrical & Electronic

Energy Efficient Resource Allocation in UAV-Enabled Mobile Edge Computing Networks

Zhaohui Yang et al.

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS (2019)

Review Engineering, Electrical & Electronic

Deep Learning With Edge Computing: A Review

Jiasi Chen et al.

PROCEEDINGS OF THE IEEE (2019)

Article Computer Science, Information Systems

Deep Deterministic Policy Gradient (DDPG)-Based Energy Harvesting Wireless Communications

Chengrun Qiu et al.

IEEE INTERNET OF THINGS JOURNAL (2019)

Article Computer Science, Information Systems

Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics

Ke Zhang et al.

IEEE INTERNET OF THINGS JOURNAL (2019)

Article Automation & Control Systems

UAV-Enhanced Intelligent Offloading for Internet of Things at the Edge

Hongzhi Guo et al.

IEEE Transactions on Industrial Informatics (2019)

Article Engineering, Aerospace

Cooperative search-attack mission planning for multi-UAV based on intelligent self-organized algorithm

Zhen Ziyang et al.

AEROSPACE SCIENCE AND TECHNOLOGY (2018)

Article Engineering, Electrical & Electronic

Multiple Moving Targets Surveillance Based on a Cooperative Network for Multi-UAV

Jingjing Gu et al.

IEEE COMMUNICATIONS MAGAZINE (2018)

Article Computer Science, Hardware & Architecture

UAV-Empowered Edge Computing Environment for Cyber-Threat Detection in Smart Vehicles

Sahil Garg et al.

IEEE NETWORK (2018)

Article Automation & Control Systems

Energy-Efficient Industrial Internet of UAVs for Power Line Inspection in Smart Grid

Zhenyu Zhou et al.

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS (2018)

Article Engineering, Electrical & Electronic

Computation Rate Maximization in UAV-Enabled Wireless-Powered Mobile-Edge Computing Systems

Fuhui Zhou et al.

IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS (2018)

Proceedings Paper Computer Science, Theory & Methods

Cooperative Computation Offloading for UAVs: A Joint Radio and Computing Resource Allocation Approach

Shichao Zhu et al.

2018 IEEE INTERNATIONAL CONFERENCE ON EDGE COMPUTING (IEEE EDGE) (2018)

Article Computer Science, Hardware & Architecture

Efficient Multi-User Computation Offloading for Mobile-Edge Cloud Computing

Xu Chen et al.

IEEE-ACM TRANSACTIONS ON NETWORKING (2016)

Article Multidisciplinary Sciences

Human-level control through deep reinforcement learning

Volodymyr Mnih et al.

NATURE (2015)

Article Engineering, Aerospace

Cooperative Search by UAV Teams: A Model Predictive Approach using Dynamic Graphs

James R. Riehl et al.

IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS (2011)

Article Automation & Control Systems

Multi-UAV cooperative search using an opportunistic learning method

Yanli Yang et al.

JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME (2007)