[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Ale et al., 2021 - Google Patents

Delay-aware and energy-efficient computation offloading in mobile-edge computing using deep reinforcement learning

Ale et al., 2021

View PDF
Document ID
4091241961655905922
Author
Ale L
Zhang N
Fang X
Chen X
Wu S
Li L
Publication year
Publication venue
IEEE Transactions on Cognitive Communications and Networking

External Links

Snippet

Internet of Things (IoT) is considered as the enabling platform for a variety of promising applications, such as smart transportation and smart city, where massive devices are interconnected for data collection and processing. These IoT applications pose a high …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00—Subject matter not provided for in other groups of this subclass
    • G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/02—Computer systems based on biological models using neural network models
    • G06N3/08—Learning methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/54—Store-and-forward switching systems
    • H04L12/56—Packet switching systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computer systems based on specific mathematical models
    • G06N7/005—Probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computer systems based on biological models
    • G06N3/12—Computer systems based on biological models using genetic models
    • G06N3/126—Genetic algorithms, i.e. information processing using digital simulations of the genetic system
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation, e.g. linear programming, "travelling salesman problem" or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00—Computer systems utilising knowledge based models
    • G06N5/04—Inference methods or devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation, e.g. computer aided management of electronic mail or groupware; Time management, e.g. calendars, reminders, meetings or time accounting
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network-specific arrangements or communication protocols supporting networked applications
    • H04L67/10—Network-specific arrangements or communication protocols supporting networked applications in which an application is distributed across nodes in the network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
    • G06F—ELECTRICAL DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for programme control, e.g. control unit
    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements

Similar Documents

Publication Publication Date Title
Ale et al. Delay-aware and energy-efficient computation offloading in mobile-edge computing using deep reinforcement learning
Huang et al. AoI-aware energy control and computation offloading for industrial IoT
Jiang et al. Stacked autoencoder-based deep reinforcement learning for online resource scheduling in large-scale MEC networks
Liu et al. Online computation offloading and resource scheduling in mobile-edge computing
Lin et al. Resource management for pervasive-edge-computing-assisted wireless VR streaming in industrial Internet of Things
Tak et al. Federated edge learning: Design issues and challenges
Zhang et al. MR-DRO: A fast and efficient task offloading algorithm in heterogeneous edge/cloud computing environments
Hu et al. An efficient online computation offloading approach for large-scale mobile edge computing via deep reinforcement learning
Xie et al. A reinforcement learning approach for optimizing the age-of-computing-enabled IoT
Hammami et al. On-policy vs. off-policy deep reinforcement learning for resource allocation in open radio access network
Li et al. Multi-edge collaborative offloading and energy threshold-based task migration in mobile edge computing environment
Liu et al. Fine-grained offloading for multi-access edge computing with actor-critic federated learning
Qu et al. Stochastic cumulative DNN inference with RL-aided adaptive IoT device-edge collaboration
Tang et al. Joint service deployment and task scheduling for satellite edge computing: A two-timescale hierarchical approach
Qin et al. User‐Edge Collaborative Resource Allocation and Offloading Strategy in Edge Computing
Ansere et al. Quantum deep reinforcement learning for dynamic resource allocation in mobile edge computing-based IoT systems
Li et al. Dynamic user-scheduling and power allocation for SWIPT aided federated learning: A deep learning approach
Heidarpour et al. Soft actor–critic-based computation offloading in multiuser MEC-enabled IoT—a lifetime maximization perspective
Peng et al. Task offloading in multiple-services mobile edge computing: A deep reinforcement learning algorithm
Zhao et al. MEDIA: An incremental DNN based computation offloading for collaborative cloud-edge computing
Chen et al. Joint Task and Computing Resource Allocation in Distributed Edge Computing Systems via Multi-Agent Deep Reinforcement Learning
Xie et al. Backscatter-aided hybrid data offloading for mobile edge computing via deep reinforcement learning
Wang et al. Analysis and prediction of UAV-assisted mobile edge computing systems
Rjoub et al. One-shot federated learning-based model-free reinforcement learning
Chai et al. A dynamic queuing model based distributed task offloading algorithm using deep reinforcement learning in mobile edge computing