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

Hribar et al., 2021 - Google Patents

Energy-aware deep reinforcement learning scheduling for sensors correlated in time and space

Hribar et al., 2021

View PDF
Document ID
17501409033591456097
Author
Hribar J
Marinescu A
Chiumento A
DaSilva L
Publication year
Publication venue
IEEE Internet of Things Journal

External Links

Snippet

Millions of battery-powered sensors deployed for monitoring purposes in a multitude of scenarios, eg, agriculture, smart cities, industry, etc., require energy-efficient solutions to prolong their lifetime. When these sensors observe a phenomenon distributed in space and …
Continue reading at arxiv.org (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02BINDEXING SCHEME RELATING TO CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. INCLUDING HOUSING AND APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B60/00Information and communication technologies [ICT] aiming at the reduction of own energy use
    • Y02B60/50Techniques for reducing energy-consumption in wireless communication networks
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00Data switching networks
    • H04L12/02Details
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04WWIRELESS COMMUNICATIONS NETWORKS
    • H04W52/00Power Management, e.g. TPC [Transmission Power Control], power saving or power classes
    • H04W52/02Power saving arrangements
    • H04W52/0209Power saving arrangements in terminal devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA 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
    • G06Q10/00Administration; Management
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00Network-specific arrangements or communication protocols supporting networked applications

Similar Documents

Publication Publication Date Title
Hatami et al. AoI minimization in status update control with energy harvesting sensors
Hribar et al. Energy-aware deep reinforcement learning scheduling for sensors correlated in time and space
Agarwal et al. Intelligent fault-tolerance data routing scheme for IoT-enabled WSNs
KR101837580B1 (en) A communications system, an access network node and a method of optimising energy consumed in a communication network
Hribar et al. Using correlated information to extend device lifetime
US11762446B2 (en) Method and system for energy aware scheduling for sensors
Dias et al. Adapting sampling interval of sensor networks using on-line reinforcement learning
Chen et al. On-demand transmission for edge-assisted remote control in industrial network systems
Li et al. Multi-sensor transmission power control for remote estimation through a SINR-based communication channel
Sarkar et al. VSF: An energy-efficient sensing framework using virtual sensors
Khot et al. Cellular automata-based optimised routing for secure data transmission in wireless sensor networks
El Ghazi et al. Energy efficient teaching-learning-based optimization for the discrete routing problem in wireless sensor networks
Hribar et al. Utilising correlated information to improve the sustainability of internet of things devices
Hribar et al. Using deep Q-learning to prolong the lifetime of correlated internet of things devices
Geraldo Filho et al. ResiDI: Towards a smarter smart home system for decision-making using wireless sensors and actuators
Das et al. Context-aware resource management in multi-inhabitant smart homes: A framework based on Nash H-learning
Liu et al. Timely updates in MEC-assisted status update systems: Joint task generation and computation offloading scheme
Laidi et al. On predicting sensor readings with sequence modeling and reinforcement learning for energy-efficient iot applications
Gong et al. Lifelong learning for minimizing age of information in Internet of Things networks
Al-Hawawreh et al. An online model to minimize energy consumption of IoT sensors in smart cities
Choudhary et al. A dynamic K-means-based clustering algorithm using fuzzy logic for CH selection and data transmission based on machine learning
Zhang et al. Attack-resistant, energy-adaptive monitoring for smart farms: Uncertainty-aware deep reinforcement learning approach
Silva et al. A Cluster-based Approach to provide Energy-Efficient in WSN
Wu et al. AIMD rule-based duty cycle scheduling in wireless sensor networks using quartile-directed adaptive genetic algorithm
Mughal et al. An intelligent Hybrid‐Q Learning clustering approach and resource management within heterogeneous cluster networks based on reinforcement learning