Deep-Reinforcement-Learning-Based Computation Offloading for Servicing Dynamic Demand in Multi-UAV-Assisted IoT Network

In wireless networks, meeting the performance requirements of all tasks solely with Internet of Things (IoT) devices is challenging due to their limited computational power and battery capacity. Given their flexibility and mobility, the application of unmanned aerial vehicles (UAVs) in the context o...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	IEEE internet of things journal Ročník 11; číslo 10; s. 17249 - 17263
Hlavní autoři:	Lin, Na, Bai, Lu, Hawbani, Ammar, Guan, Yunchong, Mao, Chaojin, Liu, Zhi, Zhao, Liang
Médium:	Journal Article
Jazyk:	angličtina japonština
Vydáno:	Piscataway IEEE 15.05.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Autonomous aerial vehicles Computation offloading Deep learning deep reinforcement learning (DRL) Dynamic scheduling Edge computing Energy consumption Greedy algorithms Heuristic algorithms Internet of Things Mixed integer Mobile computing mobile edge computing (MEC) Nonlinear programming Resource management Servers Task analysis Task scheduling unmanned aerial vehicle (UAV) Unmanned aerial vehicles Wireless networks
ISSN:	2327-4662, 2327-4662
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!