Abstract
More and more users are attracted by P2P networks characterized by decentralization, autonomy and anonymity. The management and optimization of P2P networks have become the important research contents. This paper presents a framework for network self-evolving problem based on distributed swarm intelligence, which is achieved by the collaboration of different nodes. Each node, as an independent agent, only has the information of its local topology. Through the consensus method, each node searches for an evolving structure to evolve its local topology. The self-evolving of each node’s local topology makes the whole topology converge to the optimal topology model. In the experiments, two simulated examples under different network topologies illustrate the feasibility of our approach.
Supported by the National Key Research and Development Program of China under Grant No. 2019YFB1005203.
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Acknowledgements
The authors would like to thank the anonymous reviewers for their insightful comments and suggestions on this paper. This work was supported in part by the National Key Research and Development Program of China under Grant No. 2019YFB1005203.
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Tian, C., Zhang, Y., Yin, T. (2022). A Framework for Network Self-evolving Based on Distributed Swarm Intelligence. In: Groen, D., de Mulatier, C., Paszynski, M., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2022. ICCS 2022. Lecture Notes in Computer Science, vol 13351. Springer, Cham. https://doi.org/10.1007/978-3-031-08754-7_24
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