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In this paper, we propose an efficient resource discovery framework allowing pure unstructured peer-to-peer systems to respond to requests at run time with a high success rate while preserving the local autonomy of member machines. There are five units in the proposed framework that respectively gather information about the status of resources, make decisions, detect the states of member machines,...
In this work, we address competition among autonomous cognitive radios (CRs) which are competing for frequency bands, and model their interactions. We design auction mechanisms with and without an entry fee and define utility functions based on the total achieved capacity per unit price. We equip the CRs with a learning algorithm in order to bid more efficiently. Our considered network consists of...
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