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A Reinforcement Learning Based Framework for Prediction of Near Likely Nodes in Data-Centric Mobile Wireless Networks
EURASIP Journal on Wireless Communications and Networking
Data-centric storage provides energy-efficient data dissemination and organization for the increasing amount of wireless data. 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 cannot bedoi:10.1155/2010/319275 fatcat:xwk2ctffgrcrtissjdmdunrzba