| Title |
Joint slice-based spreading factor and transmission power optimization in LoRa smart city networks |
| ID_Doc |
37128 |
| Authors |
Dawaliby, S; Bradai, A; Pousset, Y |
| Title |
Joint slice-based spreading factor and transmission power optimization in LoRa smart city networks |
| Year |
2021 |
| Published |
|
| DOI |
10.1016/j.iot.2019.100121 |
| Abstract |
The fifth generation (5G) wireless networks is expected to support an all-connected world with a multitude internet of things (IoT) applications. To reach this goal, network slicing is adopted to provide flexibility in managing heterogeneous IoT networks. The focus of this paper is to implement an adaptive dynamic network slicing mechanism in a Lora-based smart city network using a maximum likelihood estimation. The latter avoids resource starvation and is combined with a slice-based optimization method that configures spreading factor and transmission power parameters in a way that maximizes the performance utility in each slice. Simulation results performed in realistic LoRa scenarios highlight the utility of our proposition in respecting defined quality of service (QoS) thresholds in terms of delay, throughput, energy consumption and improving reliability while providing a complete isolation between LoRa slices. (C) 2019 Elsevier B.V. All rights reserved. |
| Author Keywords |
Internet of Things (IoT); Smart city; LoRa; Slice optimization; Resource allocation; Dynamic network slicing |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Science Citation Index Expanded (SCI-EXPANDED) |
| EID |
WOS:000695695900008 |
| WoS Category |
Computer Science, Information Systems; Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Computer Science; Engineering; Telecommunications |
| PDF |
https://hal.science/hal-02301022/file/S2542660519301908.pdf
|