TY - JOUR
T1 - Market model for resource allocation in emerging sensor networks with reinforcement learning
AU - Zhang, Yue
AU - Song, Bin
AU - Zhang, Ying
AU - Du, Xiaojiang
AU - Guizani, Mohsen
N1 - Publisher Copyright:
© 2016 by the authors; licensee MDPI, Basel, Switzerland.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management.
AB - Emerging sensor networks (ESNs) are an inevitable trend with the development of the Internet of Things (IoT), and intend to connect almost every intelligent device. Therefore, it is critical to study resource allocation in such an environment, due to the concern of efficiency, especially when resources are limited. By viewing ESNs as multi-agent environments, we model them with an agent-based modelling (ABM) method and deal with resource allocation problems with market models, after describing users’ patterns. Reinforcement learning methods are introduced to estimate users’ patterns and verify the outcomes in our market models. Experimental results show the efficiency of our methods, which are also capable of guiding topology management.
KW - Agent-based modelling
KW - Emerging sensor networks
KW - Internet of Things
KW - Market model
KW - Reinforcement learning
KW - Resource allocation
KW - Topology management
UR - http://www.scopus.com/inward/record.url?scp=85000644770&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85000644770&partnerID=8YFLogxK
U2 - 10.3390/s16122021
DO - 10.3390/s16122021
M3 - Article
AN - SCOPUS:85000644770
SN - 1424-8220
VL - 16
JO - Sensors (Switzerland)
JF - Sensors (Switzerland)
IS - 12
M1 - 2021
ER -