DocumentCode :
3191502
Title :
Research on Load Balancing Based on Multi-agent in Ubiquitous Networks
Author :
Jiang Qing ; Xu Mei ; Tang Lun ; Chen Qian-bin
Author_Institution :
Key Lab. of Mobile Commun. Technol., Chongqing Univ. of Posts & Telecommun., Chongqing, China
Volume :
3
fYear :
2010
fDate :
11-12 May 2010
Firstpage :
10
Lastpage :
13
Abstract :
Next-generation Network wireless Communication System has a variety of access modes. In order to solute how to select a proper access network under this feature and to realize the load balancing, A ubiquitous networks configuration based on multi-agent is proposed in this paper, use multi-agent Q-learning to realize the load balancing in Ubiquitous Networks with heterogeneous Radio Access Technologies (RAT). Agent in the Radio Access Network (RAN) collects radio access networks´ loading information, then feed back them by communicate between agents. Agents get optimal policy through trial-and-error and interaction with wireless environment and learn to allocate the proper RAN for each session. Simulation results show that the proposed algorithm realizes the autonomy of resource control through the agents´ online learning process and achieves the load balancing through the agents´ coordinate.
Keywords :
learning (artificial intelligence); multi-agent systems; radio access networks; resource allocation; ubiquitous computing; agents online learning process; heterogeneous radio access technologies; load balancing; multiagent; next-generation network wireless communication system; radio access network; ubiquitous networks; Computer networks; Intelligent agent; Intelligent networks; Learning; Load management; Multiagent systems; Q factor; Radio access networks; Resource management; Wireless communication; Multi-agent; Q–learning; Radio Access Technology; Ubiquitous Network; load balancing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
Type :
conf
DOI :
10.1109/ICICTA.2010.756
Filename :
5522679
Link To Document :
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