Deep reinforcement learning for resource management on network slicing: A survey
JA Hurtado Sánchez, K Casilimas… - Sensors, 2022 - mdpi.com
Network Slicing and Deep Reinforcement Learning (DRL) are vital enablers for achieving
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
5G and 6G networks. A 5G/6G network can comprise various network slices from unique or …
A decade of research in fog computing: relevance, challenges, and future directions
SN Srirama - Software: Practice and Experience, 2024 - Wiley Online Library
Recent developments in the Internet of Things (IoT) and real‐time applications, have led to
the unprecedented growth in the connected devices and their generated data. Traditionally …
the unprecedented growth in the connected devices and their generated data. Traditionally …
Collaborative computation offloading and resource allocation in multi-UAV-assisted IoT networks: A deep reinforcement learning approach
In the fifth-generation (5G) wireless networks, Edge-Internet-of-Things (EIoT) devices are
envisioned to generate huge amounts of data. Due to the limitation of computation capacity …
envisioned to generate huge amounts of data. Due to the limitation of computation capacity …
AI-Powered Edge Computing in Cloud Ecosystems: Enhancing Latency Reduction and Real-Time Decision-Making in Distributed Networks
P Nama, M Bhoyar, S Chinta - Well Testing Journal, 2024 - welltestingjournal.com
Integrating edge computing with AI offers a profoundly enabling opportunity to reduce
latency and allow real-time decision-making in distributed networks within cloud …
latency and allow real-time decision-making in distributed networks within cloud …
Joint optimization of energy consumption and time delay in IoT-fog-cloud computing environments using NSGA-II metaheuristic algorithm
V Jafari, MH Rezvani - Journal of Ambient Intelligence and Humanized …, 2023 - Springer
Today, there exists a growing demand for Internet of Things (IoT) services in the form of
vehicle networks, smart cities, augmented reality, virtual reality, positioning systems, and so …
vehicle networks, smart cities, augmented reality, virtual reality, positioning systems, and so …
Exploring the potential of distributed computing continuum systems
Computing paradigms have evolved significantly in recent decades, moving from large room-
sized resources (processors and memory) to incredibly small computing nodes. Recently …
sized resources (processors and memory) to incredibly small computing nodes. Recently …
[HTML][HTML] Atmosphere: Context and situational-aware collaborative IoT architecture for edge-fog-cloud computing
Abstract The Internet of Things (IoT) has grown significantly in popularity, accompanied by
increased capacity and lower cost of communications, and overwhelming development of …
increased capacity and lower cost of communications, and overwhelming development of …
A novel strategy to achieve bandwidth cost reduction and load balancing in a cooperative three-layer fog-cloud computing environment
Recently, IoT (Internet of Things) has been an attractive area of research to develop smart
home, smart city environment. IoT sensors generate data stream continuously and majority …
home, smart city environment. IoT sensors generate data stream continuously and majority …
Decentralized edge-to-cloud load balancing: Service placement for the Internet of Things
The Internet of Things (IoT) requires a new processing paradigm that inherits the scalability
of the cloud while minimizing network latency using resources closer to the network edge …
of the cloud while minimizing network latency using resources closer to the network edge …
Serverless data pipeline approaches for IoT data in fog and cloud computing
With the increasing number of Internet of Things (IoT) devices, massive amounts of raw data
is being generated. The latency, cost, and other challenges in cloud-based IoT data …
is being generated. The latency, cost, and other challenges in cloud-based IoT data …