Abstract
In this paper we study a dynamic version of the Decentralized Packet Clustering (DPC) Problem. For a network consisting of routers and application servers the DPC problem is to find a good clustering for packets that are sent between the servers through the network. The clustering is done according to a data vector in the packets. In the dynamic version of DPC the packets data vector can change. The proposed algorithms to solve the dynamic DPC are inspired by the odor recognition system of ants. We analyze the new algorithms for situations with different strengths of dynamic change and for different number of routers in the network.
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Merkle, D., Middendorf, M., Scheidler, A. (2005). Dynamic Decentralized Packet Clustering in Networks. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2005. Lecture Notes in Computer Science, vol 3449. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-32003-6_60
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DOI: https://doi.org/10.1007/978-3-540-32003-6_60
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25396-9
Online ISBN: 978-3-540-32003-6
eBook Packages: Computer ScienceComputer Science (R0)