A distributed adaptive landmark clustering algorithm based onmOverlayandlearning automatafor topology mismatch problem in unstructured peer‐to‐peer networks
Ali Mohammad Saghiri, Mohammad Reza Meybodi · International Journal of Communication Systems · 2015
Summary Peer‐to‐peer networks are overlay networks that are built on top of communication networks that are called underlay networks. In these networks, peers are unaware of the underlying networks, so the peers choose their neighbors without considering the underlay positions, and therefore, the resultant overlay network may have mismatches with its underlying network, causing redundant end‐to‐end delay. Landmark clustering algorithms, such asmOverlay, are used to solve topology mismatch problem. In themOverlayalgorithm, the overlay network is formed by clusters in which each cluster has a landmark peer. One of the drawbacks ofmOverlayis that the selected landmark peer for each cluster is fixed during the operation of the network. Because of the dynamic nature of peer‐to‐peer networks, using a non‐adaptive landmark selection algorithm may not be appropriate. In this paper, an adaptive landmark clustering algorithm obtained from the combination ofmOverlayandlearning automatais proposed.Learning automataare used to adaptively select appropriate landmark peers for the clusters in such a way that the total communication delay will be minimized. Simulation results have shown that the proposed algorithm outperforms the existing algorithms with respect to communication delay and average round‐trip time between peers within clusters. Copyright © 2015 John Wiley & Sons, Ltd.