Abstract
In order to support very high storage utilizing untrusted peers located throughout the Internet, an adaptive-learning peer-to-peer distributed file system has been design and implemented. By moving the file system out of the laboratory environment, we are able to provide users with a virtually unlimited storage space. To support utilization of nodes beyond a local network, trusted nodes across the Internet need to be used with characteristics along the lines of scalability, availability and becoming profitable if the services are available to paid customers.
In this paper we present results from our novel adaptive-learning rule-based peer-to-peer distributed file system which is able to build a trusted distributed file system environment and enables users to securely store and retrieve their files at either trusted storage nodes or untrusted nodes that are located across the network. We further present some interesting results obtained when a rouge node is presented to the system.
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© 2004 Springer-Verlag Berlin Heidelberg
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Gradecki, J.D., Ra, I. (2004). An Adaptive-Learning Distributed File System. In: Negoita, M.G., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2004. Lecture Notes in Computer Science(), vol 3213. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30132-5_88
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DOI: https://doi.org/10.1007/978-3-540-30132-5_88
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23318-3
Online ISBN: 978-3-540-30132-5
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