Cloud-edge hybrid deep learning framework for scalable IoT resource optimization
Abstract In the dynamic environment of the Internet of Things (IoT), edge and cloud computing play critical roles in analysing and storing data from numerous connected devices to produce valuable insights. Efficient resource allocation and workload distribution are vital to ensuring continuous and r...
Saved in:
Main Authors: | Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2025-02-01
|
Series: | Journal of Cloud Computing: Advances, Systems and Applications |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13677-025-00729-w |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Securing fog computing in healthcare with a zero-trust approach and blockchain
by: Navjeet Kaur, et al.
Published: (2025-02-01) -
Service Architecture and Control Configuration Technology of Distribution-Network Edge Computing Based on Hybrid Control
by: GUO Ning, JI Tuo, LU Xiaoxing, DONG Shufeng, XIAO Maoran, JIAO Hao, XIAO Xiaolong, WU Fan
Published: (2025-02-01) -
Quantum mechanical insights into Edge-Dependent electronic properties of phosphorene nanoribbons
by: Mohammadamir Bazrafshan, et al.
Published: (2025-02-01) -
Community Participation in Programme Planning for Universal Health Coverage in India: An exploratory study
by: Yogesh Chandra, et al.
Published: (2025-02-01) -
Functional Outcome of Osteosynthesis with PHILOS in Elderly Patients: Experience at Tertiary Care Centre
by: Narendra Singh Kushwaha, et al.
Published: (2023-01-01)