Novel Optical Access Network Virtualization and Dynamic Resource Allocation Algorithms for the Internet of Things

2015 ◽  
Author(s):  
Jing Wang ◽  
Neda Cvijetic ◽  
Konstantinos Kanonakis ◽  
Ting Wang ◽  
Gee-Kung Chang
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Network Virtualization ◽  
Access Network ◽  
Dynamic Resource Allocation ◽  
The Internet ◽  
Optical Access Network ◽  
Dynamic Resource ◽  
Allocation Algorithms ◽  
The Internet Of Things

scholarly journals Large Scale Resource Allocation for the Internet of Things Network Based on ADMM

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 57192-57203 ◽  
Author(s):  
Yanhua He ◽  
Sunxuan Zhang ◽  
Liangrui Tang ◽  
Yun Ren
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Large Scale ◽  
The Internet ◽  
The Internet Of Things

EdgeABC: An architecture for task offloading and resource allocation in the Internet of Things

2020 ◽  
Vol 107 ◽  
pp. 498-508
Author(s):  
Kaile Xiao ◽  
Zhipeng Gao ◽  
Weisong Shi ◽  
Xuesong Qiu ◽  
Yang Yang ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
The Internet ◽  
The Internet Of Things ◽  
Task Offloading

scholarly journals Deep Grid Scheduler for 5G NB-IoT Uplink Transmission

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Han Zhong ◽  
Ruize Sun ◽  
Fengcheng Mei ◽  
Yong Chen ◽  
Fan Jin ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Internet Of Things ◽  
Resource Utilization ◽  
Smart Cities ◽  
Dynamic Resource Allocation ◽  
Smart Manufacturing ◽  
Resource Allocation Algorithm ◽  
Allocation Algorithm ◽  
Environment Model ◽  
Dynamic Resource

Since the birth of narrowband Internet of Things (NB-IoT), the Internet of Things (IoT) industry has made a considerable progress in the application for smart cities, smart manufacturing, and healthcare. Therefore, the number of UEs is increasing exponentially, which brings considerable pressure to the efficient resource allocation for the bandwidth and power constrained NB-IoT networks. In view of the conventional algorithms that cannot dynamically adjust resource allocation, resulting in a low resource utilization and prone to resource fragmentation, this paper proposes a double deep Q-network (DDQN)-based NB-IoT dynamic resource allocation algorithm. It first builds an NB-IoT environment model based on the real environment. Then, the DDQN algorithm interacts with the NB-IoT environment model to learn and optimize resource allocation strategies until it converges to the optimum. Finally, the simulation results show that the DDQN-based NB-IoT dynamic resource allocation algorithm is better than the traditional algorithm in the resource utilization, average transmission rate, and UE average queuing time.

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