Suchergebnisse - efficient Q‐learning based computation offloading algorithm

Q‐learning based computation offloading for multi‐UAV‐enabled cloud‐edge computing networks

Autoren: Meng Wang Shuo Shi Shushi Gu et al.

Quelle: IET Communications. 14:2481-2490

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Zugangs-URL: https://ietresearch.onlinelibrary.wiley.com/doi/pdfdirect/10.1049/iet-com.2019.1184
https://ietresearch.onlinelibrary.wiley.com/doi/pdf/10.1049/iet-com.2019.1184
https://doi.org/10.1049/iet-com.2019.1184
https://ietresearch.onlinelibrary.wiley.com/doi/10.1049/iet-com.2019.1184
https://digital-library.theiet.org/content/journals/10.1049/iet-com.2019.1184
https://dblp.uni-trier.de/db/journals/iet-com/iet-com14.html#WangSGGQ20

ImanRHT/QECO: A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing

Autoren: Iman Rahmati

Schlagwörter: DRL, deep reinforcement learning, MEC, Mobile edge computing, quality of experience, DQN, LSTM, computation task offloading

Computation Offloading for Workflow in Mobile Edge Computing Based on Deep Q-Learning

Autoren: Mingfang Ma Songtao Guo Xin Su et al.

Quelle: 2019 28th Wireless and Optical Communications Conference (WOCC). :1-5

Schlagwörter: 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology, 7. Clean energy

Zugangs-URL: https://dblp.uni-trier.de/db/conf/wocc/wocc2019.html#ZhuGMFL0GJ19
https://ieeexplore.ieee.org/document/8770689/
https://doi.org/10.1109/WOCC.2019.8770689

Twin delayed deep deterministic policy gradient-based intelligent computation offloading for IoT

Autoren: Siguang Chen Bei Tang Kun Wang

Quelle: Digital Communications and Networks, Vol 9, Iss 4, Pp 836-845 (2023)

Schlagwörter: Deep reinforcement learning, Computation offloading, 0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, Fog computing, Information technology, 02 engineering and technology, Resource allocation, T58.5-58.64, 7. Clean energy

Zugangs-URL: https://doaj.org/article/6b11b52c7125444ab8938bc917e5095c

Joint computation offloading and task caching for multi-user and multi-task MEC systems: reinforcement learning-based algorithms.

Autoren: Elgendy, Ibrahim A. Zhang, Wei-Zhe He, Hui et al.

Quelle: Wireless Networks (10220038). Apr2021, Vol. 27 Issue 3, p2023-2038. 16p.

Schlagwörter: *REINFORCEMENT learning, *PROBLEM solving, *MOBILE computing, *EDGE computing, *ALGORITHMS, *NONLINEAR equations

Task Offloading and Scheduling Based on Mobile Edge Computing and Software-defined Networking

Autoren: Fatimah Azeez Rawdhan

Quelle: Journal of Telecommunications and Information Technology, Vol 99, Iss 1 (2025)

Schlagwörter: energy efficiency, MEC, PSO, Q-learning, scalability, scheduling, Telecommunication, TK5101-6720, Information technology, T58.5-58.64

Dateibeschreibung: electronic resource

Relation: https://www.jtit.pl/jtit/article/view/1941; https://doaj.org/toc/1899-8852

Zugangs-URL: https://doaj.org/article/c861c02dcfc64add8297c91742baf9ad

Q‐learning based computation offloading for multi‐UAV‐enabled cloud‐edge computing networks.

Autoren: Wang, Meng Shi, Shuo Gu, Shushi et al.

Quelle: IET Communications (Wiley-Blackwell); Sep2020, Vol. 14 Issue 15, p2481-2490, 10p

Schlagwörter: ARTIFICIAL intelligence, MOBILE computing, DRONE aircraft, NONLINEAR programming, CELL phones, EDGE computing

An efficient computational offloading method using deep reinforcement learning in edge-end-cloud.

Autoren: Liu, Xinrui Feng, Libo Zhang, Peiying et al.

Quelle: Ad Hoc Networks. Nov2025, Vol. 178, pN.PAG-N.PAG. 1p.

Schlagwörter: Reinforcement learning, Edge computing, Energy consumption, Cloud computing, Blockchains

Task Offloading and Scheduling Based on Mobile Edge Computing and Software-defined Networking.

Autoren: Rawdhan, Fatimah Azeez¹ fatimah.azeez@uomustansiriyah.edu.iq

Quelle: Journal of Telecommunications & Information Technology. 2025, Issue 1, p30-37. 8p.

Schlagwörter: Multi-objective optimization, Particle swarm optimization, Mobile computing, Software-defined networking, Resource allocation

Adaptive and Energy-Efficient IoT Routing via DOS-RL with Bayesian Hyperparameter Tuning in SDN-Driven Architectures.

Autoren: Selvi, M. Senthamil Sudha, L.

Quelle: Cuestiones de Fisioterapia; 2025, Vol. 54 Issue 3, p173-192, 20p

Schlagwörter: WIRELESS sensor networks, SOFTWARE-defined networking, REINFORCEMENT learning, SENSOR networks, NETWORK performance

Fuzzy clustering based scheduling algorithm for minimizing the tasks completion time in cloud computing environment.

Autoren: Alharbe NR; Computer Science Department, Collage of Computer Sciences and Engineering, Taibah University, 46537, Madinah, Saudi Arabia. nrharbe@taibahu.edu.sa.

Quelle: Scientific reports [Sci Rep] 2025 Jun 04; Vol. 15 (1), pp. 19505. Date of Electronic Publication: 2025 Jun 04.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: PubMed not MEDLINE; MEDLINE

An integrated queuing and certainty factor theory model for efficient edge computing in remote patient monitoring systems.

Autoren: RahimiZadeh K Beheshti A Javadi B et al.

Quelle: Scientific reports [Sci Rep] 2025 Nov 21. Date of Electronic Publication: 2025 Nov 21.

Publikationsart: Journal Article

Info zur Zeitschrift: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Blockchain-Based Communication for Digital Twins

Autoren: Lv, Z. Li, Y. Qiao, L. et al.

Quelle: Advances in Blockchain Technology for Cyber Physical Systems. :193-210

Schlagwörter: Computer Sciences, Datavetenskap (datalogi), Blockchain, Data security, Digital twins, Edge computing, Resource allocation, Computation theory, Deep learning, Digital storage, Engineering education, Information management, Learning algorithms, Reinforcement learning, Allocation methods, Block-chain, Creation process, Log storages, Reinforcement Learning theories, Resource allocation algorithms, Resources allocation, Storage systems, Users' satisfactions, Security of data

Zugangs-URL: https://gup.ub.gu.se/publication/320653

A game-based deep reinforcement learning approach for energy-efficient computation in MEC systems.

Autoren: Chen, Miaojiang Liu, Wei Wang, Tian et al.

Quelle: Knowledge-Based Systems. Jan2022, Vol. 235, pN.PAG-N.PAG. 1p.

Schlagwörter: *DEEP learning, *DATA transmission systems, *REINFORCEMENT learning, *ASYNCHRONOUS learning, *FREQUENCY division multiple access, *TIME division multiple access, *ALGORITHMS

Collaborative framework for UAVs-assisted mobile edge computing: a proximity policy optimization approach.

Autoren: Du, Ruizhong Cao, Bowen Gao, Yan

Quelle: Journal of Supercomputing; May2024, Vol. 80 Issue 8, p10485-10510, 26p

Schlagwörter: MOBILE computing, EDGE computing, DEEP reinforcement learning, REINFORCEMENT learning, MARKOV processes

DDPG-Based Computation Offloading Strategy for Maritime UAV.

Autoren: Zhao, Ziyue Xu, Yanli Yu, Qianlian

Quelle: Electronics (2079-9292); Sep2025, Vol. 14 Issue 17, p3376, 19p

Schlagwörter: EDGE computing, RESOURCE allocation, DRONE aircraft, INTERNET of things, REINFORCEMENT learning, DISTRIBUTED computing

Energy-efficient UAV-enabled computation offloading for industrial internet of things: a deep reinforcement learning approach.

Autoren: Shi, Shuo Wang, Meng Gu, Shushi et al.

Quelle: Wireless Networks (10220038); Jul2024, Vol. 30 Issue 5, p3921-3934, 14p

Schlagwörter: DEEP reinforcement learning, REINFORCEMENT learning, INTERNET of things, EDGE computing, COMMUNICATION infrastructure, MULTIAGENT systems, DISTRIBUTED algorithms

A Vehicle-Assisted Computation Offloading Algorithm Based on Proximal Policy Optimization in Vehicle Edge Networks.

Autoren: Chen, Geng Xu, Xianjie Zeng, Qingtian et al.

Quelle: Mobile Networks & Applications; Dec2023, Vol. 28 Issue 6, p2041-2055, 15p

Schlagwörter: INTERNET access, INCENTIVE (Psychology), RESOURCE allocation, NETWORK performance, ALGORITHMS, SMART devices

Reinforcement learning based task offloading of IoT applications in fog computing: algorithms and optimization techniques.

Autoren: Allaoui, Takwa Gasmi, Kaouther Ezzedine, Tahar

Quelle: Cluster Computing; Nov2024, Vol. 27 Issue 8, p10299-10324, 26p

Schlagwörter: DEEP reinforcement learning, REINFORCEMENT learning, PROCESS capability, MATHEMATICAL optimization, INTERNET of things

Dual-Q network deep reinforcement learning-based computation offloading method for industrial internet of things.

Autoren: Du, Ruizhong Wu, Jinru Gao, Yan

Quelle: Journal of Supercomputing; Nov2024, Vol. 80 Issue 17, p25590-25615, 26p

Schlagwörter: DEEP reinforcement learning, DATA privacy, MACHINE learning, MOBILE computing, INTERNET of things