Cargando…
Real-Time Task Assignment Approach Leveraging Reinforcement Learning with Evolution Strategies for Long-Term Latency Minimization in Fog Computing
The emerging fog computing technology is characterized by an ultralow latency response, which benefits a massive number of time-sensitive services and applications in the Internet of things (IoT) era. To this end, the fog computing infrastructure must minimize latencies for both service delivery and...
Autores principales: | Mai, Long, Dao, Nhu-Ngoc, Park, Minho |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163362/ https://www.ncbi.nlm.nih.gov/pubmed/30150577 http://dx.doi.org/10.3390/s18092830 |
Ejemplares similares
-
An analytical model to minimize the latency in healthcare internet-of-things in fog computing environment
por: Shukla, Saurabh, et al.
Publicado: (2019) -
Latency-Aware Task Scheduling for IoT Applications Based on Artificial Intelligence with Partitioning in Small-Scale Fog Computing Environments
por: Lim, JongBeom
Publicado: (2022) -
Fog computing at industrial level, architecture, latency, energy, and security: A review
por: Caiza, Gustavo, et al.
Publicado: (2020) -
Intelligent air defense task assignment based on hierarchical reinforcement learning
por: Liu, Jia-yi, et al.
Publicado: (2022) -
A Novel Low-Latency and Energy-Efficient Task Scheduling Framework for Internet of Medical Things in an Edge Fog Cloud System
por: Alatoun, Kholoud, et al.
Publicado: (2022)