DocumentCode :
629880
Title :
Network selection for autonomous mobile devices
Author :
Mahmoodi, Toktam
Author_Institution :
Centre for Telecommun. Res., King´s Coll. London, London, UK
fYear :
2013
fDate :
18-20 March 2013
Firstpage :
125
Lastpage :
127
Abstract :
The rise of mixed mobile networks of WiFi, cellular small cells and traditional base stations, opens new challenges in optimising user´s access to the networks. In fact, this mix of Radio Access Networks (RAN) become more heterogeneous as various technologies such as LTE, UMTS and WiMAX operates at the small cells. To fully utilise the capacity of such rich field of heterogeneous wireless connectivity, mobile devices should be able to select RAN (or a combination of RANs) for their connection and depending on their need. The proposed algorithm here is based on an autonomous agent at the mobile node, and assisted by integration of distributed cloud services. The ultimate aim is the design of RAN selection algorithm owned by autonomous and intelligent user agents that can significantly improve the user´s Quality of Experience (QoE) in terms of network coverage, data rate, and battery life-time.
Keywords :
Long Term Evolution; WiMax; cellular radio; cloud computing; radio access networks; wireless LAN; LTE; QoE; RAN; UMTS; Wi-Fi; WiMAX; autonomous mobile devices; autonomous user agents; base stations; battery lifetime; cellular small cells; data rate; distributed cloud services; intelligent user agents; network coverage; network selection; quality of experience; radio access networks; Algorithm design and analysis; Mobile communication; Mobile computing; Mobile handsets; Quality of service; Radio access networks; Wireless communication; heterogenous mobile networks; meta learning; mobile cloud computing; network selection;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless On-demand Network Systems and Services (WONS), 2013 10th Annual Conference on
Conference_Location :
Banff, AB
Print_ISBN :
978-1-4799-0747-2
Type :
conf
DOI :
10.1109/WONS.2013.6578336
Filename :
6578336
Link To Document :
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