Abstract
In this chapter, we discuss the issues related to the problem of semantic resource querying in dynamic p2p environments and present the current approximations and successful solutions, with a special emphasis on their scalability. We focus on the use of nature-inspired metaheuristics, especially the ant colony optimization, and describe in detail the fundamental challenges an efficient p2p resources querying algorithm must overcome. The outlined approaches are evaluated in terms of the quality and completeness of the searches, as well as the algorithmic overhead. We introduce the notions of information diffusion in a p2p network as a means of combating the resource redistribution, and multipheromone approaches, that are often used to enable efficient semantic queries.
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Krynicki, K., Jaen, J. (2017). Ant Colony Optimization for Semantic Searching of Distributed Dynamic Multiclass Resources. In: Patnaik, S., Yang, XS., Nakamatsu, K. (eds) Nature-Inspired Computing and Optimization. Modeling and Optimization in Science and Technologies, vol 10. Springer, Cham. https://doi.org/10.1007/978-3-319-50920-4_11
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DOI: https://doi.org/10.1007/978-3-319-50920-4_11
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