DocumentCode :
3085081
Title :
Prediction of near likely nodes in data-centric mobile wireless networks
Author :
Chen, Yingying ; Wang, Hui ; Zheng, Xiuyuan ; Yang, Jie
Author_Institution :
Dept. of Electr. & Comput. Eng., Stevens Inst. of Technol., Hoboken, NJ, USA
fYear :
2009
fDate :
18-21 Oct. 2009
Firstpage :
1
Lastpage :
7
Abstract :
As the increasing amount of data is collected in mobile wireless networks for emerging pervasive applications, data-centric storage provides energy-efficient data dissemination and organization. One of the approaches in data-centric storage is that the nodes that collected data will transfer their data to other neighboring nodes that store the similar type of data. However, when the nodes are mobile, type-based data distribution alone cannot provide robust data storage and retrieval, since the nodes that store similar types may move far away and can not be easily reachable in the future. In order to minimize the communication overhead and achieve efficient data retrieval in data-centric mobile environments, we propose a fully distributed neighborhood prediction scheme that utilizes past node trajectory information to determine the near likely node in the future as the best content distributee. We developed two methods that predict the future neighborhood based on the correlations of the past trajectories. Our extensive simulation results demonstrate that our prediction approaches can effectively and efficiently predict the future neighborhood with high accuracy.
Keywords :
information dissemination; information retrieval; mobile computing; mobile radio; storage management; data organization; data retrieval; data transfer; data-centric mobile wireless networks; data-centric storage; distributed neighborhood prediction scheme; energy-efficient data dissemination; near likely nodes prediction; past node trajectory information; pervasive applications; type-based data distribution; Content based retrieval; Energy efficiency; Energy storage; Information retrieval; Memory; Mobile communication; Predictive models; Robustness; Trajectory; Wireless networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Military Communications Conference, 2009. MILCOM 2009. IEEE
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-5238-5
Electronic_ISBN :
978-1-4244-5239-2
Type :
conf
DOI :
10.1109/MILCOM.2009.5379936
Filename :
5379936
Link To Document :
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